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Top 23 information-extraction Open-Source Projects
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PaddleNLP
π Easy-to-use and powerful NLP and LLM library with π€ Awesome model zoo, supporting wide-range of NLP tasks from research to industrial applications, including πText Classification, π Neural Search, β Question Answering, βΉοΈ Information Extraction, π Document Intelligence, π Sentiment Analysis etc.
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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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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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RomBuster
RomBuster is a router exploitation tool that allows to disclosure network router admin password.
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awesome-bioie
𧫠A curated list of resources relevant to doing Biomedical Information Extraction (including BioNLP)
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odinson
Odinson is a powerful and highly optimized open-source framework for rule-based information extraction. Odinson couples a simple, yet powerful pattern language that can operate over multiple representations of text, with a runtime system that operates in near real time.
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IRCP
A robust information gathering tool for large scale reconnaissance on Internet Relay Chat servers π°οΈ (by internet-relay-chat)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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
Check out kor
First time coming across this, looks very cool! Definitely some ideas there that I'd like to implement for osintbuddy. Another project I'm going to be taking some ideas from is: https://github.com/ail-project/ail-framework - a modular framework to analyse potential information leaks
> The objective of this competition is to link spans of text in clinical notes with specific topics in the SNOMED CT clinical terminology. Participants will train models based on real-world doctor's notes which have been de-identified and annotated with SNOMED CT concepts by medically trained professionals. This is the largest publicly available dataset of labelled clinical notes, and you can be one of the first to use it!
NER: Named Entity Recognition: https://en.wikipedia.org/wiki/Named-entity_recognition
awsome-medical-coding-nlp: https://github.com/acadTags/Awesome-medical-coding-NLP
awesome-ehr-deep-learning: https://github.com/hurcy/awesome-ehr-deeplearning
awesome-ner: https://github.com/smiyawaki0820/awesome-ner
awesome-bioie > Research groups: https://github.com/caufieldjh/awesome-bioie#groups-active-in...
SNOMED-CT as RDF: https://sphn-semantic-framework.readthedocs.io/en/latest/ext...
Project mention: A LLM trained to follow annotation guidelines, for information extraction tasks | news.ycombinator.com | 2023-10-30
Project mention: [D] Finetuning for text extraction (e.g. scientific sources) | /r/MachineLearning | 2023-06-11Odinson
Project mention: IRCP: A robust information gathering tool for large scale reconnaissance on Internet Relay Chat servers | /r/netsec | 2023-06-07
Conventional Knowledge Graph Construction (KGC) approaches typically follow the static information extraction paradigm with a closed set of pre-defined schema. As a result, such approaches fall short when applied to dynamic scenarios or domains, whereas a new type of knowledge emerges. This necessitates a system that can handle evolving schema automatically to extract information for KGC. To address this need, we propose a new task called schema-adaptable KGC, which aims to continually extract entity, relation, and event based on a dynamically changing schema graph without re-training. We first split and convert existing datasets based on three principles to build a benchmark, i.e., horizontal schema expansion, vertical schema expansion, and hybrid schema expansion; then investigate the schema-adaptable performance of several well-known approaches such as Text2Event, TANL, UIE and GPT-3. We further propose a simple yet effective baseline dubbed AdaKGC, which contains schema-enriched prefix instructor and schema-conditioned dynamic decoding to better handle evolving schema. Comprehensive experimental results illustrate that AdaKGC can outperform baselines but still have room for improvement. We hope the proposed work can deliver benefits to the community. Code and datasets will be available in https://github.com/zjunlp/AdaKGC.
information-extraction related posts
- Pydentic in prompt engineering
- 27-Jun-2023
- Guidance on creating a very lightweight model that does one task very well
- Kor: Extract structured data using LLMs
- Kor: Extract structured data using LLMs
- Google Local Results AI Parser
- Ruby gem to parse structured data from Google Local Search Results
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A note from our sponsor - WorkOS
workos.com | 23 Apr 2024
Index
What are some of the best open-source information-extraction projects? This list will help you:
Project | Stars | |
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1 | PaddleNLP | 11,386 |
2 | MITIE | 2,892 |
3 | DeepKE | 2,891 |
4 | InvoiceNet | 2,382 |
5 | kor | 1,501 |
6 | awesome-document-understanding | 1,108 |
7 | 007-TheBond | 1,030 |
8 | ail-framework | 495 |
9 | RomBuster | 422 |
10 | medaCy | 412 |
11 | MedCAT | 407 |
12 | awesome-bioie | 300 |
13 | GoLLIE | 204 |
14 | awesome-hungarian-nlp | 205 |
15 | huspacy | 147 |
16 | htmldate | 106 |
17 | minie | 88 |
18 | targetedSummarization | 86 |
19 | stargather | 67 |
20 | odinson | 66 |
21 | KIE_invoice_minimal | 49 |
22 | IRCP | 44 |
23 | AdaKGC | 16 |
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