Triple

T18094313
Position Surface form Disambiguated ID Type / Status
Subject Mutineer E433044 entity
Predicate recordLabel P1500 FINISHED
Object Giant Records 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: Giant Records | Statement: [Mutineer, recordLabel, Giant Records]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Giant Records
Context triple: [Mutineer, recordLabel, Giant Records]
  • A. Giant Records chosen
    Giant Records was an American record label, active primarily in the 1990s, known for releasing rock, pop, and alternative music by artists such as Oingo Boingo.
  • B. Galaxy Records
    Galaxy Records is a jazz-focused record label known for releasing albums by prominent artists such as pianist Red Garland.
  • C. King Records
    King Records was an influential American independent record label, particularly known for its R&B, country, and early rock and roll releases in the mid-20th century.
  • D. Landmark Records
    Landmark Records was a jazz-focused record label known for producing albums by prominent artists such as pianist Mulgrew Miller during the 1980s and 1990s.
  • E. Glass Records
    Glass Records is an independent British record label known for releasing influential alternative and indie music during the 1980s.
  • 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_69d8b907d05c819083cc3bd6021089e6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dd1b670081908e1e1083436da04e completed April 19, 2026, 1:48 p.m.
Created at: April 10, 2026, 10:27 a.m.