Triple

T866877
Position Surface form Disambiguated ID Type / Status
Subject People E18721 entity
Predicate hasOnlineEdition P57 FINISHED
Object People.com E18721 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: People.com | Statement: [People, hasOnlineEdition, People.com]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: People.com
Context triple: [People, hasOnlineEdition, People.com]
  • A. Moviefone
    Moviefone is an online service that provides movie showtimes, tickets, and related film information to consumers.
  • B. E!
    E! is an American cable television network best known for its entertainment news, celebrity gossip, and pop culture–focused reality programming.
  • C. People
    People is a widely read American weekly magazine focusing on celebrity news, human-interest stories, and popular culture.
  • D. People (magazine) chosen
    People is a popular American weekly magazine best known for its celebrity news, human-interest stories, and annual features like "Sexiest Man Alive."
  • E. Forbes
    Forbes is a historic rural town in central-west New South Wales, Australia, known for its agricultural industry and heritage architecture along the Lachlan River.
  • 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_69a4938ce8688190a24bdfef82ba7d21 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac7e12b0819084d25b9a66888a91 completed March 1, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3c9e7ec819081d58634fe0efdcb completed March 4, 2026, 3:15 a.m.
Created at: March 1, 2026, 7:39 p.m.