kiril-me/rep-task
Recognizing Textual Entailment
This project helps evaluate if a statement (hypothesis) can be logically concluded from a given text. You provide pairs of text and a related hypothesis, and it tells you if the hypothesis is true (entailment), false (contradiction), or unrelated (neutral) to the text. This is useful for anyone working with language understanding, such as developers building smart assistants, search engines, or question-answering systems.
No commits in the last 6 months.
Use this if you need to determine the logical relationship between two pieces of text, such as for improving search relevance, chatbot responses, or information extraction.
Not ideal if you are looking for a simple keyword matching tool or a solution for analyzing individual words rather than the semantic relationship between sentences.
Stars
9
Forks
5
Language
Jupyter Notebook
License
—
Category
Last pushed
May 20, 2017
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/kiril-me/rep-task"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
hyperquest-hq/hyperbase
A foundational library for Semantic Hypergraphs
smilelight/lightKG
基于Pytorch和torchtext的知识图谱深度学习框架。
KRLabsOrg/rulechef
Learn rule-based models from examples using LLM-powered synthesis. Replace expensive LLM calls...
qq547276542/Agriculture_KnowledgeGraph
农业知识图谱(AgriKG):农业领域的信息检索,命名实体识别,关系抽取,智能问答,辅助决策
totogo/awesome-knowledge-graph
A curated list of Knowledge Graph related learning materials, databases, tools and other resources