Triple

T16438971
Position Surface form Disambiguated ID Type / Status
Subject Take Back the City E399247 entity
Predicate recordLabel P1500 FINISHED
Object Fiction Records E399253 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: Fiction Records | Statement: [Take Back the City, recordLabel, Fiction Records]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fiction Records
Context triple: [Take Back the City, recordLabel, Fiction Records]
  • A. Fiction Records chosen
    Fiction Records is a British record label best known for releasing influential alternative and rock music, including work by bands such as The Cure and Snow Patrol.
  • B. Fantasy Records
    Fantasy Records is an American independent record label best known for its influential jazz catalog, including releases by artists like Dave Brubeck and Vince Guaraldi.
  • C. One Records
    One Records is a music label known for releasing hip-hop projects, including work by rapper Fashawn.
  • D. Fontana Records
    Fontana Records is a British record label known for releasing a wide range of pop, rock, and jazz recordings, particularly during the 1960s and 1970s.
  • E. Festival Records
    Festival Records was a prominent Australian record label known for signing and releasing music by major artists such as Olivia Newton-John.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32ba720a48190b0b412225e993e52 completed April 18, 2026, 6:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0060746c308190b67ff7c4646e10de completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:10 a.m.