Tootfinder

Opt-in global Mastodon full text search. Join the index!

No exact results. Similar results found.
@NFL@darktundra.xyz
2025-10-02 13:56:16

Yankees even series with Red Sox; Dodgers move onto NLDS; Big Ten eyeing $2 billion private equity deal

cbssports.com/mlb/news/yankees

Yankees even series with Red Sox; Dodgers move onto NLDS; Big Ten eyeing $2 billion private equity deal
Plus, Brock Purdy is one of many 49ers out against the Rams on Thursday night

@arXiv_csCL_bot@mastoxiv.page
2025-09-24 10:48:24

Are most sentences unique? An empirical examination of Chomskyan claims
Hiram Ring
arxiv.org/abs/2509.19108 arxiv.org/pdf/2509.19108…

Are most sentences unique? An empirical examination of Chomskyan claims
A repeated claim in linguistics is that the majority of linguistic utterances are unique. For example, Pinker (1994: 10), summarizing an argument by Noam Chomsky, states that "virtually every sentence that a person utters or understands is a brand-new combination of words, appearing for the first time in the history of the universe." With the increased availability of large corpora, this is a claim that can be empirically investigated. The current paper addresses the question by using the NLTK …

@BBC6MusicBot@mastodonapp.uk
2025-08-26 09:44:43

🇺🇦 #NowPlaying on #BBC6Music's #LaurenLaverne
The Chambers Brothers:
🎵 Time Has Come Today
#TheChambersBrothers
open.spotify.com/track/4NlDSFD

@arXiv_csCL_bot@mastoxiv.page
2025-09-16 12:21:37

Is 'Hope' a person or an idea? A pilot benchmark for NER: comparing traditional NLP tools and large language models on ambiguous entities
Payam Latifi
arxiv.org/abs/2509.12098

Is 'Hope' a person or an idea? A pilot benchmark for NER: comparing traditional NLP tools and large language models on ambiguous entities
This pilot study presents a small-scale but carefully annotated benchmark of Named Entity Recognition (NER) performance across six systems: three non-LLM NLP tools (NLTK, spaCy, Stanza) and three general-purpose large language models (LLMs: Gemini-1.5-flash, DeepSeek-V3, Qwen-3-4B). The dataset contains 119 tokens covering five entity types (PERSON, LOCATION, ORGANIZATION, DATE, TIME). We evaluated each system's output against the manually annotated gold standard dataset using F1-score. The res…