Automating Data Services for Multilingual Gen AI
Bitext provides custom annotation for GenAI tasks, like model training and evaluation, and for NLP tasks like entity extraction, event extraction, sentiment analysis…
Bitext automates data annotation and generation tasks for AI/NLP applications for Language Model training and evaluation. Our unique differentiator: we combine automation tools with human-in-the-loop curation, to annotate data.
Additionally, we leverage proprietary NLG (Natural Language Generation) technology to produce and augment Synthetic Training Data; as well as proprietary NLP tools for Entity Extraction, Relationship Detection, Sentiment Analysis or lemmatization, POS tagging and Phrase Extraction.
Bitext also provides off-the-shelf datasets for GenAI tasks (synthetically generated conversational datasets in 20 verticals), and for NLP tasks (manually curated resources like morphological dictionaries, synonyms dictionaries and ontologies).
DAL: Automation Tools for Data Annotation and Labelling
We provide custom Data Annotation and Labeling (DAL) services for (Generative) AI. We focus on the automation of human annotation, building custom Human-in-the-loop (HITL) pipelines to improve data annotation speed and quality with custom software applications. A few examples:
- We use custom and proprietary data sources of linguistic knowledge like ontologies or morphological dictionaries
- We use NLP tools, like entity detection or sentiment annotation, to pre-annotate the data for human annotators
- We train AI models to perform pre-annotation tasks so human annotators are relieved from mechanical tasks
NLG: Synthetic Text Generation Tools to generate custom datasets
Currently focused on assistants/chatbots, Bitext NLG toolset generates custom training and
eval datasets for your chatbots.
These datasets are annotated for:
- Language register (colloquial, formal, etc.)
- Offensive language
- Syntactic complexity
- Spelling and grammar checking
We also tag speech/voice transcription errors (customized for different ASR engines) and other linguistic features like lemma, POS, morphological attributes, entities, and more
Pre-Built Datasets to train and evaluate your assistant/chatbot
Bitext has produced different vertical datasets to instantly train and evaluate your bot
These datasets are already tagged with:
- Language register (colloquial, formal…)
- Offensive language
- Syntactic complexity…
- Spelling and grammar checking
- Speech/voice transcription errors (customized for different ASR engines)
- Linguistic features like lemma, POS, morphological attributes, entities, and many more
NLP: Text Annotation Tools for NLP Tasks in 70+ Languages
Bitext provides core linguistic tools to automatically pre-annotate custom corpora & datasets:
- Lemma, POS and morphological attributes
- Named Entities like Person Name, Last Name, Company, etc.
- Key Phrases or Constituents
- Topic-Level sentiment analysis
- Offensive language
NLP: Lexical and Semantic Data in 70+ Languages
Core linguistic data for any NLP application: Lexical Data and Semantic Data
Lexical Data:
Bitext produces lexical dictionaries that contain detailed information like POS, morphological
attributes, frequency in corpora, and more
Bitext has produced these dictionaries for 77 languages (including Indian and Asian languages)
and 25 language variants (including 6 variants for Spanish, Canadian French, etc.)
.
These dictionaries are used for a wide range of use cases:
- Lemmatization for search and indexing
- Lemmatization for topic modelling
- Spelling and grammar checking
- Key phrase extraction
- Corpus annotation
Semantic Data:
Bitext produces synonym dictionaries both for general purposes (complementing WordNet) and for specific verticals like Finance, Human Resources, and Legal.
All synonyms include linguistic attributes like POS, inflected forms, frequency in Bitext in general, and vertical-specific corpora.
Custom Tagging
The main focus of Bitext’s recent consulting projects has been the generation of instructional prompts for AI models. These projects typically involve training models that can answer questions by extracting information from financial reports and tables as well as by performing calculations. Given an answer, we generate a prompt that is linguistically correct, as well as the set of calculation steps to reach the answer – both the questions and the steps are validated by financial experts for accuracy and relevance.
Most of our projects have three ingredients:
- Linguistic structure: our linguists prepare the necessary linguistic data and tools
- Scientific/specialist structure: our linguists work with subject-matter experts, typically to create ontologies to map domain knowledge
- Tagging/annotation: our software generates tagged data by combining linguistic data and ontologies. Then, subject matter experts validate the output
Use Cases
As an example, we’ve worked on projects with medical/healthcare experts to validate the creation and annotation of linguistic resources, incorporating knowledge such as semantic equivalence between texts and paraphrasing.
We have also worked in multiple languages (German, French, Japanese, etc.) and language variants.
MADRID, SPAIN
Camino de las Huertas, 20, 28223 Pozuelo
Madrid, Spain
SAN FRANCISCO, USA
541 Jefferson Ave Ste 100, Redwood City
CA 94063, USA