Why pay more? A simple and efficient named entity recognition system for tweets
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
'NER for tweets' is a problem that many people have studied.
“third, 'NER for tweets' is a problem that many people have studied [15, 33, 49].”
From Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences (2024) · cites this paper as [49]
Cited by
Sorted by citations
Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences
Shankar, S., Zamfirescu-Pereira, J. D., Hartmann, B., Parameswaran, A., & Arawjo, I. (2024) · Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3654777.3676450 · Cited by 151 · see citing works
- Authors
- Suman, C., Reddy, S. M., Saha, S., & Bhattacharyya, P.
- Affiliations
- Indian Institute of Technology Patna (IN)
- Corresponding author
- Suman, Chanchal
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 167
- Pages
- 114101
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W3093291461
- Cited by
- 27
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 9 · 2022: 6 · 2021: 3 · 2020: 1
- FWCI
- 1.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Expert Systems with Applications (publishedVersion)
- Funders
- Science and Engineering Research Board
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- named entity recognition, tweets, multimodal named entity recognition, handcrafted features, character-level features, hashtags, hyperlinks, imaging features, bidirectional LSTM, convolutional neural networks, conditional random fields
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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