Triple

T3174803
Position Surface form Disambiguated ID Type / Status
Subject Michael Arrington E66435 entity
Predicate formerWebsite P69 FINISHED
Object https://techcrunch.com/ E10979 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: https://techcrunch.com/ | Statement: [Michael Arrington, formerWebsite, https://techcrunch.com/]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: https://techcrunch.com/
Context triple: [Michael Arrington, formerWebsite, https://techcrunch.com/]
  • A. TechCrunch chosen
    TechCrunch is a leading technology news website and media platform known for its coverage of startups, Silicon Valley, and the tech industry.
  • B. Engadget
    Engadget is a technology news and reviews website that covers consumer electronics, gadgets, and digital culture.
  • C. ESPNews
    ESPNews is an American cable sports television channel owned by ESPN that focuses on sports news, highlights, and analysis.
  • D. BNN Bloomberg
    BNN Bloomberg is a Canadian specialty television channel and media brand focused on business and financial news, formed through a partnership between Bell Media’s Business News Network and Bloomberg.
  • E. MIT Technology Review
    MIT Technology Review is a technology-focused media outlet and magazine known for in-depth reporting and analysis on emerging technologies and their impact on society, business, and policy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad8586a34c8190944c63ec11a8de1a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada670c800819098937783e2b05c7a completed March 8, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b235f16e60819091cbdb76130ecc40 completed March 12, 2026, 3:41 a.m.
Created at: March 8, 2026, 3:06 p.m.