#text annotation
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habiledata · 10 months ago
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Explore the vital role of text annotation within AI and machine learning in our latest blog post. As a key component of natural language processing, effective annotation enables machines to comprehend human language.
We have discussed certain challenges of managing annotation projects, including data quality and team collaboration, offering best practices to streamline your processes for optimal results.
Read Our Complete Article Here: https://www.habiledata.com/blog/text-annotation-best-practices/
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cogitotech · 27 days ago
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Why Do Companies Outsource Text Annotation Services?
Building AI models for real-world use requires both the quality and volume of annotated data. For example, marking names, dates, or emotions in a sentence helps machines learn what those words represent and how to interpret them.
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At its core, different applications of AI models require different types of annotations. For example, natural language processing (NLP) models require annotated text, whereas computer vision models need labeled images.
While some data engineers attempt to build annotation teams internally, many are now outsourcing text annotation to specialized providers. This approach speeds up the process and ensures accuracy, scalability, and access to professional text annotation services for efficient, cost-effective AI development.
In this blog, we will delve into why companies like Cogito Tech offer the best, most reliable, and compliant-ready text annotation training data for the successful deployment of your AI project. What are the industries we serve, and why is outsourcing the best option so that you can make an informed decision!
What is the Need for Text Annotation Training Datasets?
A dataset is a collection of learning information for the AI models. It can include numbers, images, sounds, videos, or words to teach machines to identify patterns and make decisions. For example, a text dataset may consist of thousands of customer reviews. An audio dataset might contain hours of speech. A video dataset could have recordings of people crossing the street.
Text annotation services are crucial for developing language-specific or NLP models, chatbots, applying sentiment analysis, and machine translation applications. These datasets label parts of text, such as named entities, sentiments, or intent, so algorithms can learn patterns and make accurate predictions. Industries such as healthcare, finance, e-commerce, and customer service rely on annotated data to build and refine AI systems.
At Cogito Tech, we understand that high-quality reference datasets are critical for model deployment. We also understand that these datasets must be large enough to cover a specific use case for which the model is being built and clean enough to avoid confusion. A poor dataset can lead to a poor AI model.
How Do Text Annotation Companies Ensure Scalability?
Data scientists, NLP engineers, and AI researchers need text annotation training datasets for teaching machine learning models to understand and interpret human language. Producing and labeling this data in-house is not easy, but it is a serious challenge. The solution to this is seeking professional help from text annotation companies.
The reason for this is that as data volumes increase, in-house annotation becomes more challenging to scale without a strong infrastructure. Data scientists focusing on labeling are not able to focus on higher-level tasks like model development. Some datasets (e.g., medical, legal, or technical data) need expert annotators with specialized knowledge, which can be hard to find and expensive to employ.
Diverting engineering and product teams to handle annotation would have slowed down core development efforts and compromised strategic focus. This is where specialized agencies like ours come into play to help data engineers support their need for training data. We also provide fine-tuning, quality checks, and compliant-labeled training data, anything and everything that your model needs.
Fundamentally, data labeling services are needed to teach computers the importance of structured data. For instance, labeling might involve tagging spam emails in a text dataset. In a video, it could mean labeling people or vehicles in each frame. For audio, it might include tagging voice commands like “play” or “pause.”
Why is Text Annotation Services in Demand?
Text is one of the most common data types used in AI model training. From chatbots to language translation, text annotation companies offer labeled text datasets to help machines understand human language.
For example, a retail company might use text annotation to determine whether customers are happy or unhappy with a product. By labeling thousands of reviews as positive, negative, or neutral, AI learns to do this autonomously.
As stated in Grand View Research, “Text annotation will dominate the global market owing to the need to fine-tune the capacity of AI so that it can help recognize patterns in the text, voices, and semantic connections of the annotated data”.
Types of Text Annotation Services for AI Models
Annotated textual data is needed to help NLP models understand and process human language. Text labeling companies utilize different types of text annotation methods, including:
Named Entity Recognition (NER) NER is used to extract key information in text. It identifies and categorizes raw data into defined entities such as person names, dates, locations, organizations, and more. NER is crucial for bringing structured information from unstructured text.
Sentiment Analysis It means identifying and tagging the emotional tone expressed in a piece of textual information, typically as positive, negative, or neutral. This is commonly used to analyze customer reviews and social media posts to review public opinion.
Part-of-Speech (POS) Tagging It refers to adding metadata like assigning grammatical categories, such as nouns, pronouns, verbs, adjectives, and adverbs, to each word in a sentence. It is needed for comprehending sentence structure so that the machines can learn to perform downstream tasks such as parsing and syntactic analysis.
Intent Classification Intent classification in text refers to identifying the purpose behind a user’s input or prompt. It is generally used in the context of conversational models so that the model can classify inputs like “book a train,” “check flight,” or “change password” into intents and enable appropriate responses for them.
Importance of Training Data for NLP and Machine Learning Models
Organizations must extract meaning from unstructured text data to automate complex language-related tasks and make data-driven decisions to gain a competitive edge.
The proliferation of unstructured data, including text, images, and videos, necessitates text annotation to make this data usable as it powers your machine learning and NLP systems.
The demand for such capabilities is rapidly expanding across multiple industries:
Healthcare: Medical professionals employed by text annotation companies perform this annotation task to automate clinical documentation, extract insights from patient records, and improve diagnostic support.
Legal: Streamlining contract analysis, legal research, and e-discovery by identifying relevant entities and summarizing case law.
E-commerce: Enhancing customer experience through personalized recommendations, automated customer service, and sentiment tracking.
Finance: In order to identify fraud detection, risk assessment, and regulatory compliance, text annotation services are needed to analyze large volumes of financial text data.
By investing in developing and training high-quality NLP models, businesses unlock operational efficiencies, improve customer engagement, gain deeper insights, and achieve long-term growth.
Now that we have covered the importance, we shall also discuss the roadblocks that may come in the way of data scientists and necessitate outsourcing text annotation services.
Challenges Faced by an In-house Text Annotation Team
Cost of hiring and training the teams: Having an in-house team can demand a large upfront investment. This refers to hiring, recruiting, and onboarding skilled annotators. Every project is different and requires a different strategy to create quality training data, and therefore, any extra expenses can undermine large-scale projects.
Time-consuming and resource-draining: Managing annotation workflows in-house often demands substantial time and operational oversight. The process can divert focus from core business operations, such as task assignments, to quality checks and revisions.
Requires domain expertise and consistent QA: Though it may look simple, in actual, text annotation requires deep domain knowledge. This is especially valid for developing task-specific healthcare, legal, or finance models. Therefore, ensuring consistency and accuracy across annotations necessitates a rigorous quality assurance process, which is quite a challenge in terms of maintaining consistent checks via experienced reviewers.
Scalability problems during high-volume annotation tasks: As annotation needs grow, scaling an internal team becomes increasingly tough. Expanding capacity to handle large influx of data volume often means getting stuck because it leads to bottlenecks, delays, and inconsistency in quality of output.
Outsource Text Annotation: Top Reasons and ROI Benefits
The deployment and success of any model depend on the quality of labeling and annotation. Poorly labeled information leads to poor results. This is why many businesses choose to partner with Cogito Tech because our experienced teams validate that the datasets are tagged with the right information in an accurate manner.
Outsourcing text annotation services has become a strategic move for organizations developing AI and NLP solutions. Rather than spending time managing expenses, businesses can benefit a lot from seeking experienced service providers. Mentioned below explains why data scientists must consider outsourcing:
Cost Efficiency: Outsourcing is an economical way that can significantly reduce labor and infrastructure expenses compared to hiring internal workforce. Saving costs every month in terms of salary and infrastructure maintenance costs makes outsourcing a financially sustainable solution, especially for startups and scaling enterprises.
Scalability: Outsourcing partners provide access to a flexible and scalable workforce capable of handling large volumes of text data. So, when the project grows, the annotation capacity can increase in line with the needs.
Speed to Market: Experienced labeling partners bring pre-trained annotators, which helps projects complete faster and means streamlined workflows. This speed helps businesses bring AI models to market more quickly and efficiently.
Quality Assurance: Annotation providers have worked on multiple projects and are thus professional and experienced. They utilize multi-tiered QA systems, benchmarking tools, and performance monitoring to ensure consistent, high-quality data output. This advantage can be hard to replicate internally.
Focus on Core Competencies: Delegating annotation to experts has one simple advantage. It implies that the in-house teams have more time refining algorithms and concentrate on other aspects of model development such as product innovation, and strategic growth, than managing manual tasks.
Compliance & Security: A professional data labeling partner does not compromise on following security protocols. They adhere to data protection standards such as GDPR and HIPAA. This means that sensitive data is handled with the highest level of compliance and confidentiality. There is a growing need for compliance so that organizations are responsible for utilizing technology for the greater good of the community and not to gain personal monetary gains.
For organizations looking to streamline AI development, the benefits of outsourcing with us are clear, i.e., improved quality, faster project completion, and cost-effectiveness, all while maintaining compliance with trusted text data labeling services.
Use Cases Where Outsourcing Makes Sense
Outsourcing to a third party rather than performing it in-house can have several benefits. The foremost advantage is that our text annotation services cater to the needs of businesses at multiple stages of AI/ML development, which include agile startups to large-scale enterprise teams. Here’s how:
Startups & AI Labs Quality and reliable text training data must comply with regulations to be usable. This is why early-stage startups and AI research labs often need compliant labeled data. When startups choose top text annotation companies, they save money on building an internal team, helping them accelerate development while staying lean and focused on innovation.
Enterprise AI Projects Big enterprises working on production-grade AI systems need scalable training datasets. However, annotating millions of text records at scale is challenging. Outsourcing allows enterprises to ramp up quickly, maintain annotation throughput, and ensure consistent quality across large datasets.
Industry-specific AI Models Sectors such as legal and healthcare need precise and compliant training data because they deal with personal data that may violate individual rights while training models. However, experienced vendors offer industry-trained professionals who understand the context and sensitivity of the data because they adhere to regulatory compliance, which benefits in the long-term and model deployment stages.
Conclusion
There is a rising demand for data-driven solutions to support this innovation, and quality-annotated data is a must for developing AI and NLP models. From startups building their prototypes to enterprises deploying AI at scale, the demand for accurate, consistent, and domain-specific training data remains.
However, managing annotation in-house has significant limitations, as discussed above. Analyzing return on investment is necessary because each project has unique requirements. We have mentioned that outsourcing is a strategic choice that allows businesses to accelerate project deadlines and save money.
Choose Cogito Tech because our expertise spans Computer Vision, Natural Language Processing, Content Moderation, Data and Document Processing, and a comprehensive spectrum of Generative AI solutions, including Supervised Fine-Tuning, RLHF, Model Safety, Evaluation, and Red Teaming.
Our workforce is experienced, certified, and platform agnostic to accomplish tasks efficiently to give optimum results, thus reducing the cost and time of segregating and categorizing textual data for businesses building AI models. Original Article : Why Do Companies Outsource Text Annotation Services?
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maruful009 · 1 year ago
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Expert Data Annotator Machine Learning
I'm Md. Maruful Islam is a proficient Bangladeshi data annotator trainer. At the moment, I consider it an honour to be employed by Acme AI, the leader in the data annotation industry. Throughout my career, I've gotten better at using a range of annotation tools, including SuperAnnotate, Kili, Cvat, Tasuki, FastLabel, and others.
I am a well-respected professional in the field, having produced consistently excellent annotations. My certifications for GDPR, ISO 27001, and ISO 9001 further guarantee that privacy and data security regulations are adhered to.
I sincerely hope you will give my application some thought. As a data annotator, I'd like to know more about this project and provide recommendations based on my knowledge.
Fiveer-https://www.fiverr.com/s/vqgwlLUpwork-https://www.upwork.com/services/product/design-ai-segmentation-labeling-bounding-box-for-precision-1746946743155208192?ref=project_share
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haivoai · 2 years ago
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Text Annotation with HAIVO AI: Empowering Natural Language Processing and Machine Learning
Explore HAIVO AI's text annotation services, your key to advancing natural language processing and text annotation machine learning. Unleash the potential of your text data projects with our expertise.
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just-bee-lieve · 1 year ago
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the funeral
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wedarkacademia · 2 years ago
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Yesterday I was the Moon by Noor Unnahar
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inbetweencoffees · 6 months ago
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no sleep, no coffee🌛
Just like the night before I slept less than 4 hours tonight, yay…Our coffee machine didn’t feel like doing its job at 6.30am (me too, my dear, me too), so the only thing that made me feel somewhat alive was todays sunset. Since the term is almost over we’re not doing too much in classes anymore. Gladly that means I can more or less relax until February. Except for homework and teachers getting on my nerves (my tutor huh). Who didn’t get on my nerves though was a friend of mine! They asked if I could give them feedback on their writing samples for their uni applications and I really enjoyed reading and reviewing it! It was a mix of short stories, text excerpts and poems; their last poem was my personal favourite :)
Now: watching soccer match, hoping to sleep >4h
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windienine · 9 months ago
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everyone has to be a little less mean to themselves about not reading enough books. letting go of reading as a pride thing is the first step to relearning how to actually enjoy reading for pleasure again. it's totally fine to start with a novella or with a comic or with a field guide or with literature meant for someone younger instead of being mad at yourself for not grokking ulysses in a week. just vary your diet and you'll be good.
i'm a literature scholar, i'm the one who has to be strict with myself about page counts and citations. you all? do what you want, just read and have fun.
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blackhholes · 2 months ago
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Monstrosity in Teen Wolf
Hybridity Is the New Metamorphosis by Harvey L. Hix / Skin Shows: Gothic Horror and the Technology of Monsters by Judith Halberstam / Monstrosity: The Human Monster in Visual Culture by Alexa Wright
Written for @teenwolf-meta‘s Meta May Monday theme: beast
Monstrosity and what, precisely, makes a monster is a topic that is discussed both within the text and the larger narrative of Teen Wolf. The most direct mention of monsters vs monstrosity is in *Monstrous* when Lydia tells Meredith “Not all monsters do monstrous things” referring here to Scott, which Meredith then flips back onto Lydia herself. It’s obvious to see here that the show makes a clear differentiation between what it means to be a monster and what it means to be monstrous. To be a monster means to be something unnatural it’s particularly about the outward facing part of a person, this is mainly seen with the shapeshifters who undergo a physical transformation which marks them as something different than humans, but Meredith referring to Lydia as a monster means that it’s not only the physical attributes which makes someone a monster. Being a monster is less about what you are and more about what you aren’t. Once you’re no longer able to be comfortably placed within the category of human you are a monster. This form of monster isn’t a negative attribute though, it’s a neutral one. It simply describes that the person is not a human. 
Acting monstrous is a negative attribute within the show, humans and monsters alike can act monstrous. Monstrosity is therefore not a description of person but instead a description of character. One of the most potent examples of this is in *Fury* where the viewer sees three different factions of characters. Matt is a human so he is per definition not a monster but he is a monstrous human, he stalks Allison and has spent the season carrying out his revenge plan by taking away Jackson’s autonomy and forcing him to kill people. The werewolves on the other hand are monsters who aren’t monstrous, at least to the viewer, they, particularly Scott, are trying to find a way to catch Matt without having to kill him or Jackson. It’s interesting to consider that the Argents, hunters who have always equated monster to monstrosity, have become even more radical after the death of Victoria, despite Matt’s actions he isn’t their primary target when they enter the police station, Derek is. Because, to them Derek killed Victoria by biting her and turning her into a monster just as he is. Matt is an afterthought, he’s the loose end they will deal with afterwards. The Argents therefore has the opposite understanding of the situation than the viewer does.
Humanity is also an important topic within the show, humanity is something fallible. In *Lies of Omission* the scene at the end with Scott and Stiles in the rain serves as an important look into the characters’ and particularly Stiles’ understanding of what it means to be human. When he says to Scott “Some of us are human” it’s a vocalization of the idea that to be human is to make mistakes and that humanity makes a person incapable of always doing right. As opposed to the in-humanity that comes from being incapable of erring. It is preceded by Stiles saying “Not all of us can be true alphas”, throughout this conversation, and even the entire season, Stiles has started categorizing Scott as something other than human capable of humanity, it’s not the monstrous monster previously mentioned either, it’s a third category of non-human. The true alpha isn’t monstrous but he isn’t human either. To Stiles Scott has become a sort of mythologized character who always does the right thing instead of being a real person who’s standing in front of him. 
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beescake · 1 year ago
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PLEASE PLEASE MEGADUMP THE ARASOL!!! PLEAAASEE MR BEESCAKE I AM ON MY KNEES BEGGING YOU
HFHGHD GLADLY aaa i’ve been adding notes to it here and there for months but just hesitant to post it bcs im 🧍‍♂️🧍‍♂️🧍‍♂️🧍‍♂
also this is just my own takeaway of the events, it doesn’t necessarily comply to the Ultimate Truth of Canon-Alignment or represent the actual facts of what hussie intended! v sentimental smh but hopefully its still interesting to read
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i love when characters inform each other by proximity, it's one of my fave things to see in media :') it feels even more significant when two characters deliberately choose to stick together, so that when one operates, you can tell the other is similarly aligned in associative solidarity.
sollux is a keystone of this trope — whoever he aligns with is a wordless statement, a nod of approval. this stood out to me bcs the main four humans were alr friends by default, but once you reach hivebent you realize the trolls can actively choose who they want to hang out with.
and as we all know, after assessing every troll's biases/loyalties, sollux is the only one who maintains his selective preference for innately Good 👍 people.
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aradia is such a beautiful character honestly, she evokes such incredible feelings in me. she might not have been consistently written with care but the best parts of her character are truly stunning. i think it's easy to remember sollux as the self-sacrificing one bc he's so open about it (and his friends frequently react to his Moments) but when you compare him to aradia, it's always struck me
how much more. raw it is
to be so alone as an agent of time, having to orchestrate immeasurably harrowing events nobody understands or gives a fuck about
with your role painted in the story as one who must tend to the needs of the narrative, responsible to match every next note
because when you're given the capabilities, it becomes your duty to carry it out.
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it becomes expected of you to keep experimenting and arranging the machinations to work for everyone, dusting off hundreds of necessary failures to keep going
and having to be so unwavering in your drive knowing miserably that there's no one who can help you but yourself.
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or alternatively: to make things fun! so other people won't think twice about letting you go off on your own.
sure she's had some very good buds, notably thanks to Team Charge v Team Scourge antics.
and yet, at the end of the day, the one friend that kept choosing her time and time again was the friend with the highest standards.
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i can see why people like to define arasol as moirails/matesprits but surprisingly i find the nondescript, unlabeled aspect of their relationship more straightforward to understand.
there's no shortage of people who would accommodate sollux. most of the surviving trolls are his oldest friends bcs he’d chosen them well. his transparency with his feelings had built him strong friendships that won’t falter or break, regardless of how much of a dick he can be. they’ve already seen and accepted him at his worst, and they still like him for who he is.
contrast that with aradia, who'd been so approachable, friendly and reliable in her exchanges it was super fun to talk to her. but the moment she became depressed, all her connections broke down.
her friends became hesitant to interact with her (until she became god tier, “happy” and amicable again) because her gloom and resignation didn’t serve them. she dealt with it alone.
there’s def something of note here abt the disparity between the way male & female characters are written+perceived in homestuck (esp parallel arasol with davejade) but i won’t go into that lmaoo
with this in mind i like to think of sollux as a gift to her, a loyal companion given to complement and commend her resolve. she's capable of doing so much alone but hussie took the time to build her and sollux's relationship as one of a unit; a set.
the ambiguity of their status does complicate things, but i do believe it makes sense with their characters. aradia's relationship with romance is a rocky one, the dubious stringalong equius had with her is a pointed reminder that her feelings of attraction are ultimately controlled by the author writing her.
unlike the other trolls who can openly address and own up to their crushes, aradia had romantic emotions forced upon her (especially when hussie implies 'she kissed equius back on her own volition'). and it seems like her character is so intrinsically neutral abt attraction that even when forced by the almighty powers above, she's unable to retain it wholly.
however, looking back to pre-game when she could actually "choose" her own feelings, she did have a crush on sollux.
their soft spots for each other were so obvious to the point where other people could see it.
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taunting aside, when vriska comments on their unit as bf/gf it actually informs the audience that arasol's relationship is romantic in nature despite not aligning with the quadrant system.
even while dead, aradia could still describe her care for sollux, expressing that she would like to see him happy. if they had more time to explore their relationship on alternia, it's possible they could've settled in a quadrant once they grew older.
but going back to the lack of labels, their dynamic was affected once more when aradia became god tier.
to me, her ascension was both the perfect culmination and possible closure of her character. it's the light at the end of her journey toiling through countless of timelines where she had to actively assess and participate. that's why it's cool to see her being silly and having fun giving guidance, passively exploring and watching other people do their parts.
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and yet the joy of her freedom makes it hard to explore further introspection. if we take her by her word, she'd already come to terms with the hurt she's been through and forgiven those involved.
i can't help feeling attuned to how impersonal and detached it can be, to devote and meld your identity so completely with your designated position as Maid of Time until you've become hard for your old friends (and even some readers!) to personally connect to.
idk post-canon but i assume there’s some degree of similarity to be bridged here with aradia's god tier and how the hs2 humans' Ultimate forms was described as a consolidation of all their possibilities. since aradia's classpect is inherently of service to Time, going god-tier may have elevated her beyond personhood with the "game construct" possessing her entirely. sollux doesn't realize the extent of it bcs he's still mortal, but a part of him may have subconsciously understood this.
i think there is a core aspect to aradia that was lost to the dehumanizing glory of god tier — a core aspect that may have contained an element of why sollux enjoyed talking to her in the first place.
to him, aradia hadn't just been a nice girl, she was a cool girl. despite not having much in common, he's still willing to chill next to her so she's not alone while she does what needs to get done.
back on alternia, they held a mutual and equal-level regard for each other that could've definitely settled into something permanent. but now, he's placed himself in a position where he can be kept around or left behind at will. the parameters of the relationship are largely in aradia's court, so any label she suggests to identify their relationship with he's likely to accept.
but that's why it's so difficult to label it. because god tier aradia may not necessarily Want quadrants or relationship labels. rather than the initial romantic attachment, their commitment to each other had evolved into one fundamentally of companionship.
no label? ok fine. no matter what, he still thinks she's a good soul worth latching on to. the best, actually. aradia > everyone else.
even if it gets stilted at times. there's an unexpected struggle to connect when sollux's go-to default for talking points is his feelings about things, and aradia may not want to talk about emotions all the time.
not to mention god tier aradia became an observer, especially of chaos. but sollux's avoidance of involvement comes partially from his innate pressure to get involved if something goes wrong. and he can't always tell when something goes wrong, because aradia doesn't mind if things go wrong anymore.
it's a non-negotiable preference that causes them to take the occasional time apart, a new boundary that wouldn't have existed before the game and aradia's god tier.
but just like how his friends tolerated his moods, sollux accepts aradia as she is. with no quadrants, their connection doesn't break down because there's no implicit romantic expectations to be disappointed by or resentful over.
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sometimes when i see hs content that deliberately distances sollux from aradia, i assume this is the dissonance people might have felt. people might find it "easier" to be cynical about them bcs of this strange tension.
but idc lmao. grab that shit by the neck
lack of easy resolutions and cleanly tied ribbons is pretty standard of homestuck and imo it doesn't make arasol's dynamic any less incredible. with the right affection and consideration, there's still so much potential to develop the nuance of their relationship outside of the popular quadrant-based depictions.
hs has a lot of really great character compatibilities but the way aradia and sollux are in their own special orbit is why i can write this much about them in the first place. it's that frail innocence between first loves that makes it so sweet to me, two kids who grew up too fast playing guesswork without being clear where they're going.
ultimately i do think you're meant to feel a little tragedy for just how much they care for each other, even if they can't quite establish it in simple terms.
maybe they keep taking breaks to progress their own paths. maybe they remain as anchor partners while seeing other people. but even if you decide to separate them, they're still (awkwardly) texting each other updates all the while. and when they reunite it feels like coming home.
and well. more than anything, i like to believe that they do want to be exclusive.
they're just afraid. after all, they're still learning how to love, beyond the projections of the foursquare quadrant system they had inadvertently distanced themselves from since young.
they might not have everything figured out, but they'll get there eventually if you just hold them together and write them there.
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optional post-canon segment:
one of the limitations of main hs is that (monogamous) relationships are often written as the go-to solution to wrap up character growth; it's an easy "patch" to imagine characters getting their happy ending because they have a partner, and those who don't end up with someone don't get that closure (most notably jade).
hs2 reaffirms this by suggesting that aradia's character cannot progress without letting sollux go, because happily settling in a relationship automatically locks your potential.
that pathetic panel of sollux staring emptily into the sky is still my fave hs2 spoiler ngl i find the impact of their parting so emotionally provoking precisely bcs they were written in original hs to be each other's forever, coming back together again and again
but now, they're subject to the decisions of the post-canon authors who might choose to deviate from that.
it's not new for them to part, but now there's an underlying worry that her dropping him off this time might be the last time. while i think the prospect of shattering their stability to make them grow separately sounds fun on paper, no amount of me desperately hoping for a good execution is gonna guarantee it
idk. i guess prediction-wise im expecting sollux in classic dramatic-hs2 fashion to tell dave to back off aradia LMAO. otherwise it's just gon be sollux and karkat pathetically watching aradia and dave from a distance swimming in their unresolved feelings for narratively-powerful time players smh obvs it sounds corny as hell but who knows its still plausible
srsly tho i hope they take the opportunity to develop arasol's relationship in a fresh direction that doesn't hurt me too badly...... and i hope they force sollux out of his comfort zone. i like watching him struggle :-)
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moonkissedletters · 4 months ago
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Lydia Kamakaeha, from Songs; "Farewell to Thee," wr. c. April 1896
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dvchvnde · 11 months ago
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excerpt; hitchhiker au | Simon Riley x Reader gore. graphic descriptions of decomposition. implied noncon.
“You’re not real,” she whimpers, words a rough scrape out of her raw, torn throat. “You can't be real.”
He doesn't answer tonight. Silent in his appraisal, his hatred; the bloodlust rolls off of him in waves, a suffocating deluge that tangles in her chest. Heart pulsing at the base of her throat, clogging her airways. She can't breathe. Can't move. Can only watch as the man cocks his head slowly to the side in a mutated parody of consideration. Confusion. Taking her in as he stands in her doorway, massive body filling the frame in an outline of black, making him more shadow than man. An apparition that haunts her at devil's hour. Always.
The moon's glow casts a line through the open window. A pale meridian between them. 
Childishly, she thinks of hiding under her blanket. Bad things can't touch you under the covers. Curling into a ball with her eyes squeezed shut, fingers plugging her ears. Wishing for her mother. Howling for her dad. Waiting until morning when the thing haunting her finally leaves.
But he doesn't. Not tonight. 
And she knows if she tries to hide, he'll just crawl into the bed next to her—
“Fix your bumper yet?” He asks, measured in his mockery. The weight of his words makes her stomach churn. Nausea a cold, familiar comfort that tethers itself to her ribcage. “Better get that fixed before someone comes askin’ questions, pet. Clean the blood off it, too. Caused quite the nasty spill.”
His directive makes her want to curl into a ball. “I–I didn't mean to, I didn't—”
“What'd you tell everyone? Hit a deer? Left ‘im in the bushes to die? And now he's got maggots crawlin’ all around ‘is ‘ead. Eatin’ his brains clean outta ‘is skull—”
“Shut up, shut up, shut up—you’re not real! You're not real—”
The man—Simon Riley, her mind supplies bitterly, brokenly; tinged full of regret and sorrow and hatred—lashes out in an instant, moves like water, like shadows on the wall, the too bright flicker of a moving car, until he's in her face, looming over her. A massive, unclimbable wall. And she hates it. Hates when he's this close to her. Close enough to smell the stench of rotten blood that dries on his chest, the side of his head. A brown stain that sinks into the too-large frame of his chest. 
He smells of death. Sickening. Tainted with a noisome sweetness that glues in her nostrils, leaks down her throat. She can taste him there, right on her tongue. Him. Simon Riley. 
Missing, the newspapers say. But only she knows the truth. Stowed away in a facsimile of a grave by the swamps, left to rot. Here, in her bedroom. Waiting for her whenever she tries for a modicum of sleep. A veteran. A drifter. Homeless, they write, and he barked out an ugly laugh as he read over your shoulder, but said nothing else as you scrolled. Tense. Shivering in your seat, waiting for the day the police show up and arrest you. You did a terrible thing. A horrible thing. Pay for what you've done—
His hand reaches out, fingers wrapping around the delicate arch of her throat. The width spans the entirety of it until the bone china, the vulnerable slope, is clenched tight in his slick, slippery palm. Moss, she knows; it grows over his hands and feet now. The earth reclaiming the body she threw into the swamp—
“Not real?” He mocks, wrenching her closer by her throat. Pulse thudding like the wings of a hummingbird against his thumb. “Oh, pet. M’very real—”
He leans in, too, until his horrid face is lit by the sliver of pale blue moonlight. Scraps of tissue slough off of his head, skin purpling beneath the balaclava that peels off in patches. Animals, he'd told her idly, like talking about his body being eaten away by creatures was piecemeal. The jaundiced bone of his cheek pokes out from raspberry skin. It shifts when he speaks, and draws her eye to the devastation of his mouth. Jawbone visible; muscle blackened, clinging by a strip of thin tissue to his lower mandible. His teeth gleam in the light. Yellow and crooked. The rest of his face is covered under the blood soaked fabric of his mask. A small mercy, she thinks.
But the worst is his eyes. 
Once black, midnight grey, is now filmed over. Milky. And the other—
Something moves in the cherryred chasm. A long, thin black line slinks out of the gaping hole. Another. Another. From the rotten socket, a large spider emerges, crawling over the craggy pieces of his broken nose, making his decomposing body her home. 
She whimpers as the bile surges up, swallowing it down when the blue skin of his mouth peel back in a horrifying grin—
Something white falls from the corner of his eye, rolling down the slick, damp skin of his oily face in a mockery of a teardrop, the image glueing to the bone deep remorse that coils like a noose around her neck. Tighter, tighter. 
His tongue lulls out. Cold, slimy, when it flickers over the trembling ridge of her jaw. Fingers digging into her skin, stealing the warmth from her flesh. The air from her lungs. 
He'll have her like this, she knows. Always does when he gets in these moods—the kind that makes him touch her more, sink boney fingers beneath the hem of her pants, and cooing in her ear about how much he wants to eat her alive. Buzzing with some strange, electric energy. She can't run. Can't scream. 
Going to the police isn't an option when she buried a body under loose rocks and sticks. Hit and run. Vehicular manslaughter. Life over in a blink—
No. No—
She just has to wait, she thinks, her eyes slipping shut as his rancid breath curdled over the tears on her cheeks. Wait until his body rots all the way. 
Until he's nothing but bones—
Only then will this ghost finally leave her alone. 
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choco-bite · 10 months ago
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Love language 🎀
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haivoai · 2 years ago
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Unlocking Language Insights | Expert Text Annotation at Haivo AI 
Empower your natural language understanding with Haivo AI's text annotation services. From intricate linguistic nuances to machine learning integration, we provide comprehensive solutions for refining your language-focused AI applications.
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chiropteracupola · 3 months ago
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hornblower ceramics au that no one (incl. me) asked for
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diaryofruchita · 11 months ago
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ruchita, excerpt from the house on fire
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