Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects
Verified Data Provider| # | form |
lemma |
POS |
mood |
tense |
polarity |
person |
number |
politeness |
|---|---|---|---|---|---|---|---|---|---|
| 1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx |
| 2 | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx |
| 3 | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx |
| 4 | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx |
| 5 | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx |
| 6 | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx |
| 7 | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx |
| 8 | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx |
| 9 | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx |
| 10 | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx |
| ... | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx |
Data Dictionary
| Attribute | Type | Example | Mapping |
|---|---|---|---|
|
form
|
String | あ | |
|
lemma
|
String | あ | |
|
POS
|
String | interjection | |
|
mood
|
String | n/a | |
|
tense
|
String | n/a | |
|
polarity
|
String | n/a | |
|
person
|
String | n/a | |
|
number
|
String | n/a | |
|
politeness
|
String | n/a |
Description
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Frequently asked questions
What is Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects?
At Bitext, we offer advanced linguistic tools designed for automated pre-labeling of datasets to help scale Data Annotation and Labeling (DAL) projects.
What is Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects used for?
This product has 5 key use cases. bitext recommends using the data for Artificial Intelligence (AI), Data Enrichment, Data Augmentation, Data Enhancement, and Data Labeling. Global businesses and organizations buy Natural Language Processing (NLP) Data from bitext to fuel their analytics and enrichment.
Who can use Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects?
This product is best suited if you’re a Medium-sized Business or Enterprise looking for Natural Language Processing (NLP) Data. Get in touch with bitext to see what their data can do for your business and find out which integrations they provide.
Which countries does Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects cover?
This product includes data covering 240 countries like USA, China, Japan, Germany, and India. bitext is headquartered in United States of America.
How much does Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects cost?
Pricing information for Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects is available by getting in contact with bitext. Connect with bitext to get a quote and arrange custom pricing models based on your data requirements.
What is the data quality of Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects?
You can compare and assess the data quality of bitext using Datarade’s data marketplace.
What are similar products to Bitext NLP Labeling for Gen AI Data Annotation and Labeling (DAL) projects?
This Data Annotation & Labeling has 3 related products. These alternatives include Nexdata Text Annotation Services AI-assisted Labeling Text Labeling for AI & ML Text Data Natural Language Processing (NLP) Data, FileMarket 20,000 Voice Memos Multilingual Training Data for Conversational AI Machine Learning (ML) Data, and Coresignal Employee Data AI-Enriched Dataset Global / 589+ Records / Updated Weekly. You can compare the best Natural Language Processing (NLP) Data providers and products via Datarade’s data marketplace and get the right data for your use case.
