Automatic Entity Recognition and Typing in Massive Text Data
Summary: Data-driven, domain-agnostic entity recognition and typing in massive text, automatically identifying spans and assigning fine-grained types. No annotated data or handcrafted features; rapid cross-domain, multilingual adaptation across news, forums, tweets, and biomedical text. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Xiang Ren (University of Illinois Urbana-Champaign)
- 2. Ahmed El-Kishky (University of Illinois Urbana-Champaign)
- 3. Heng Ji (Rensselaer Polytechnic Institute)
- 4. Jiawei Han (University of Illinois Urbana-Champaign)
BibTeX Citation
@inproceedings{ren_sigmod16,
title = {{Automatic Entity Recognition and Typing in Massive Text Data}},
author = {Ren, Xiang and El-Kishky, Ahmed and Ji, Heng and Han, Jiawei},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2912567},
url = {https://dl.acm.org/doi/10.1145/2882903.2912567},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 65 | Freebase: A Collaboratively Created Graph Database For Structuring Human Knowledge | 2008 | SIGMOD | 0.00038697603 |
| 317 | Annotating and Searching Web Tables Using Entities, Types and Relationships | 2010 | VLDB | 0.00021402049 |
| 367 | InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables | 2012 | SIGMOD | 0.00019979463 |
| 908 | Probase: A Probabilistic Taxonomy for Text Understanding | 2012 | SIGMOD | 0.00013300624 |
| 5,246 | Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach | 2013 | VLDB | 6.3012556e-05 |
| 8,067 | Mining Quality Phrases from Massive Text Corpora | 2015 | SIGMOD | 5.4941436e-05 |
| 12,152 | Scalable Topical Phrase Mining from Text Corpora | 2015 | VLDB | 5.093636e-05 |
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