Triple

T5751363
Position Surface form Disambiguated ID Type / Status
Subject Jez Butterworth E126859 entity
Predicate givenName P17 FINISHED
Object Jeremy E162435 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: Jeremy | Statement: [Jez Butterworth, givenName, Jeremy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremy
Context triple: [Jez Butterworth, givenName, Jeremy]
  • A. Jeremy chosen
    "Jeremy" is a widely acclaimed Pearl Jam song, known for its haunting narrative about a troubled youth and its powerful, socially charged music video.
  • B. Jeremy
    Jeremy is one of the central male protagonists in the romantic comedy film "Think Like a Man," which follows a group of men whose relationships are upended when their partners start using advice from Steve Harvey’s dating book.
  • C. Jonathan
    Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
  • D. Justin
    Justin is a character in the novel "Falling Man," which explores the aftermath of the September 11 attacks and their impact on personal and collective identity.
  • E. Justin
    Justin is a central character in the 1997 science fiction horror film "Event Horizon," serving as one of the crew members who experiences the ship’s disturbing and reality-warping effects.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0288a0ea8819091ac6f965471ceee completed March 22, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a167f2508190a8dd507f237e771b completed March 23, 2026, 2:11 a.m.
Created at: March 22, 2026, 3:48 p.m.