Triple

T186373
Position Surface form Disambiguated ID Type / Status
Subject kishida230 E3989 entity
Predicate platform P1292 FINISHED
Object Twitter E3345 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: Twitter | Statement: [kishida230, platform, Twitter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Twitter
Context triple: [kishida230, platform, Twitter]
  • A. Twitter, Inc. chosen
    Twitter, Inc. was a major social media and microblogging company best known for its real-time short-message platform that shaped online news, politics, and public discourse worldwide.
  • B. Instagram
    Instagram is a popular photo and video sharing social media platform known for its visual content, stories, and influencer culture.
  • C. Facebook
    Facebook is a major global social networking platform that allows users to connect, share content, and communicate online.
  • D. Tumblr
    Tumblr is a microblogging and social networking platform known for its highly customizable blogs, fandom communities, and viral multimedia content.
  • E. Vine
    Vine was a short-form video hosting service and social media platform known for its looping six-second clips and significant cultural impact in the early 2010s.
  • 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_69a25497e2f08190a040f8c6e1842643 completed Feb. 28, 2026, 2:36 a.m.
NER Named-entity recognition batch_69a2594809288190b3d3b1283e7e0d00 completed Feb. 28, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2fd0577588190a91be504e3c9f0ab completed Feb. 28, 2026, 2:34 p.m.
Created at: Feb. 28, 2026, 2:40 a.m.