TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction
Mirrored from arXiv — NLP / Computation & Language for archival readability. Support the source by reading on the original site.
Computer Science > Computation and Language
Title:TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction
Abstract:The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery. In this context, the GutBrainIE benchmark evaluates Named Entity Recognition (NER), Named Entity Recognition and Disambiguation (NERD), and Relation Extraction (RE) systems in the gut-brain axis domain. We propose Two-stage Workflow for Information eXtraction (TWIX), an end-to-end IE pipeline featuring three interconnected modules, each leveraging a two-stage framework to solve all four GutBrainIE subtasks. Evaluation on the development and test sets shows that our method substantially outperforms the baseline by a wide margin, while also ranking first among all participant submissions across all subtasks. These results indicate that the proposed two-stage pipeline effectively improves both precision and recall in practical settings.
| Comments: | Accepted at CLEF 2026: the 17th Conference and Labs of the Evaluation Forum |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2609.00832 [cs.CL] |
| (or arXiv:2609.00832v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.00832
arXiv-issued DOI via DataCite (pending registration)
|
Access Paper:
- View PDF
- HTML (experimental)
- TeX Source
References & Citations
Bookmark
Bibliographic and Citation Tools
Code, Data and Media Associated with this Article
Demos
Recommenders and Search Tools
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
More from arXiv — NLP / Computation & Language
-
Space as an Interventional Invariant: Cross-Modal Predictive Geometry for Stratified Cities and Em-Spaced Intelligence
Sep 14
-
MAxBench: A Multinomial Concept Recovery Benchmark
Sep 14
-
R2VC: Modular Fact-Checking with Retrieval, Verification, and Confidence Calibration
Sep 14
-
What Counts as a Mistake? Annotating Recitation Events in Quran Memorization Transcripts
Sep 14
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.