Triple

T19859346
Position Surface form Disambiguated ID Type / Status
Subject Let Love In E477214 entity
Predicate featuresBandMember P15278 FINISHED
Object Thomas Wydler NE NERFINISHED

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: Thomas Wydler | Statement: [Let Love In, featuresBandMember, Thomas Wydler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Wydler
Context triple: [Let Love In, featuresBandMember, Thomas Wydler]
  • A. Thomas Wydler chosen
    Thomas Wydler is a Swiss drummer best known as a longtime member of Nick Cave and the Bad Seeds, contributing to many of their acclaimed albums and live performances.
  • B. Thomas Origer
    Thomas Origer is an American businessman best known for owning the short-lived World Football League team the Chicago Fire in the 1970s.
  • C. Thomas Flucker
    Thomas Flucker was a colonial American official and Loyalist in Massachusetts, best known as the father of Lucy Flucker, who married Revolutionary War general Henry Knox.
  • D. Frank Fluckiger
    Frank Fluckiger is an American political figure who has served as a leading official of the Constitution Party, a minor right-wing political party in the United States.
  • E. René Havard
    René Havard was a French screenwriter and actor active in mid-20th-century cinema.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586e8b648190bb650d7f2816dda1 completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.