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stanfordnlp
CoreNLP
Java2013–2024
stanfordnlp / CoreNLP

CoreNLP

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

AI & Machine LearningLanguages & Compilers
Explore on GitHubRead Hacker News discussions
7Distinct people
7Mentions
0Explicit recommenders
10.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year7 dated mentions

Observed mentions: 2013-10-23 07:38:29 UTC to 2024-01-01 16:12:16 UTC.

01232013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20182019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC110
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC000
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC000
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC202
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC303
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101

What Hacker News says

7 sources
bmc7505·Jan 1, 2024
Old enough to remember the days when Java reached near AI-level hype. Most of the advanced placement and undergraduate CS courses in the U.S. were taught in Java. There was an annual conference in San Fransisco called JavaOne/Oracle OpenWorld that rivaled the size of even NeurIPS, drawing tens of thousands of attendees each year. According to some statistics, there were 10 million Java developers and 3 billion devices running Java worldwide. I wonder what happened? Why does HN dislike Java so much? edit: Someone should really take the time to highlight all the innovative machine learning research happening in Java. The original implementation of t-SNE [1] was written in Java. Most NLP researchers have heard of CoreNLP [2], also Java. One of the earliest ML libraries, Weka [3], was written in Java and is still actively developed at the Uni
Read the rest
versity of Waikato. Noteworthy research on ML4Code specifically targets the Java language [4]. There's a bunch of published sketching algorithms for Java (e.g., DataSketches [5], t-digests, ddsketch et al.), featured in an invited talk [6] to NeurIPS this year. Just to name a few off the top of my head. [1]: https://github.com/lejon/T-SNE-Java [2]: https://github.com/stanfordnlp/CoreNLP [3]: https://www.cs.waikato.ac.nz/ml/weka/ [4]: https://openreview.net/pdf?id=bUDmRzeh3PT [5]: https://github.com/apache/datasketches-java [6]: https://nips.cc/virtual/2023/events/Invited%20Talk
In SD4J – Stable Diffusion pipeline in Java using ONNX Runtime
blandinw·May 3, 2017
(disclaimer: I work on Duckling) I don't know of any benchmarks. HeidelTime and SUTime are two solid projects... although the rule files [0][1] are a bit scary if you ask me :-). Quick thoughts: - SUTime relies on TokensRegex [2] which is similar to how Duckling parses sentences at a high-level - SUTime seems to only provide English rules - I don't know of any production use cases of either [0] https://github.com/stanfordnlp/CoreNLP/tree/master/src/edu/s... [1] https://github.com/HeidelTime/heideltime/blob/master/resourc... [2] https://nlp.stanford.edu/pubs/tokensregex-tr-2014.pdf
In Open Sourcing our new Duckling – Probabilistic Parser Rewritten in Haskell

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