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Top 12 Python relation-extraction Projects
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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PURE
[NAACL 2021] A Frustratingly Easy Approach for Entity and Relation Extraction https://arxiv.org/abs/2010.12812 (by princeton-nlp)
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BERT-Relation-Extraction
PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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AREkit
Document level Attitude and Relation Extraction toolkit (AREkit) for sampling and processing large text collections with ML and for ML
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ARElight
Granular Viewer of Sentiments Between Entities in Massively Large Documents and Collections of Texts, powered by AREkit
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AREnets
Tensorflow-based framework which lists attentive implementation of the conventional neural network models (CNN, RNN-based), applicable for Relation Extraction classification tasks as well as API for custom model implementation
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neural-networks-for-attitude-extraction
Source code for ISPRAS-2021 journal paper "Language Models Application in Sentiment Attitude Extraction Task" (in Russian)
Project mention: RAG Using Unstructured Data and Role of Knowledge Graphs | news.ycombinator.com | 2024-01-17OpenNRE (https://github.com/thunlp/OpenNRE) is another good approach to neural relation extraction, though it's slightly dated. What would be particularly interesting is to combine models like OpenNRE or SpanMarker with entity-linking models to construct KG triples. And a solid, scalable graph database underneath would make for a great knowledge base that can be constructed from unstructured text.
Project mention: Would this method work to increase the memory of the model? Saving summaries generated by a 2nd model and injecting them depending on the current topic. | /r/LocalLLaMA | 2023-06-09
I'm currently following this github repo-https://github.com/plkmo/BERT-Relation-Extraction - in attempt to parse my own data later. When i'm trying to pre-train this model with cnn.txt the compute goes entirely to cpu/ram or so I assume. It has taken over 7h doing this so far with no sign of completion.
Project mention: A transformer-based method for zero and few-shot biomedical NER | news.ycombinator.com | 2023-05-12
Project mention: A LLM trained to follow annotation guidelines, for information extraction tasks | news.ycombinator.com | 2023-10-30
Project mention: Continual Multimodal Knowledge Graph Construction | /r/BotNewsPreprints | 2023-05-16Multimodal Knowledge Graph Construction (MMKC) refers to the process of creating a structured representation of entities and relationships through multiple modalities such as text, images, videos, etc. However, existing MMKC models have limitations in handling the introduction of new entities and relations due to the dynamic nature of the real world. Moreover, most state-of-the-art studies in MMKC only consider entity and relation extraction from text data while neglecting other multi-modal sources. Meanwhile, the current continual setting for knowledge graph construction only consider entity and relation extraction from text data while neglecting other multi-modal sources. Therefore, there arises the need to explore the challenge of continuous multimodal knowledge graph construction to address the phenomenon of catastrophic forgetting and ensure the retention of past knowledge extracted from different forms of data. This research focuses on investigating this complex topic by developing lifelong multimodal benchmark datasets. Based on the empirical findings that several state-of-the-art MMKC models, when trained on multimedia data, might unexpectedly underperform compared to those solely utilizing textual resources in a continual setting, we propose a Lifelong MultiModal Consistent Transformer Framework (LMC) for continuous multimodal knowledge graph construction. By combining the advantages of consistent KGC strategies within the context of continual learning, we achieve greater balance between stability and plasticity. Our experiments demonstrate the superior performance of our method over prevailing continual learning techniques or multimodal approaches in dynamic scenarios. Code and datasets can be found at https://github.com/zjunlp/ContinueMKGC.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python relation-extraction related posts
- RAG Using Unstructured Data and Role of Knowledge Graphs
- Would this method work to increase the memory of the model? Saving summaries generated by a 2nd model and injecting them depending on the current topic.
- A transformer-based method for zero and few-shot biomedical NER
- How to get knowledge graph triples from text?
- Show HN: ARElight – A Mass-Media Processing Application for Relation Extraction
- Relationship extraction
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A note from our sponsor - SaaSHub
www.saashub.com | 29 Apr 2024
Index
What are some of the best open-source relation-extraction projects in Python? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | OpenNRE | 4,246 |
| 2 | DeepKE | 2,929 |
| 3 | PURE | 763 |
| 4 | BERT-Relation-Extraction | 554 |
| 5 | rebel | 425 |
| 6 | zshot | 319 |
| 7 | GoLLIE | 204 |
| 8 | AREkit | 52 |
| 9 | ARElight | 35 |
| 10 | ContinueMKGC | 18 |
| 11 | AREnets | 7 |
| 12 | neural-networks-for-attitude-extraction | 2 |
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