Triple

T15595743
Position Surface form Disambiguated ID Type / Status
Subject Tapestry E374886 entity
Predicate lyricist P1360 FINISHED
Object Toni Stern E374812 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: Toni Stern | Statement: [Tapestry, lyricist, Toni Stern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toni Stern
Context triple: [Tapestry, lyricist, Toni Stern]
  • A. Toni Stern chosen
    Toni Stern is an American lyricist best known for co-writing several of Carole King’s classic songs, including major tracks on the landmark album "Tapestry."
  • B. Michael Stern
    Michael Stern is an American conductor best known for his long tenure leading the Kansas City Symphony and for his work with major orchestras in the United States and abroad.
  • C. Michael Stern
    Michael Stern is an American philanthropist and real estate developer best known for founding New York City's Intrepid Sea, Air & Space Museum.
  • D. Jonathan Stern
    Jonathan Stern is an American film and television producer best known for his work on offbeat comedies such as "Wet Hot American Summer" and various projects for Adult Swim and streaming platforms.
  • E. Anna Scher
    Anna Scher is a British drama teacher and theatre director best known for founding the influential Anna Scher Theatre in London, which has trained many prominent actors.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e5f9db8819083abf80f01f32b3d completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff75655c948190aa1afa424e5270d1 completed May 9, 2026, 5:56 p.m.
Created at: April 10, 2026, 4:12 a.m.