Triple

T9997491
Position Surface form Disambiguated ID Type / Status
Subject Beautiful Ghosts E197236 entity
Predicate associatedWork P922 FINISHED
Object Cats E138399 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: Cats | Statement: [Beautiful Ghosts, associatedWork, Cats]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cats
Context triple: [Beautiful Ghosts, associatedWork, Cats]
  • A. Cats chosen
    Cats is a long-running, award-winning musical composed by Andrew Lloyd Webber, based on T.S. Eliot’s "Old Possum’s Book of Practical Cats," renowned for its distinctive costumes, choreography, and songs like "Memory."
  • B. Cats
    Cats is the informal nickname commonly used to refer to the University of Arizona’s athletic teams, the Arizona Wildcats.
  • C. CATS
    CATS is the public transit agency serving the Charlotte, North Carolina metropolitan area, operating bus, light rail, and other transportation services.
  • D. Catz
    Catz is the informal nickname for St Catharine’s College, one of the constituent colleges of the University of Cambridge.
  • E. Catz
    Catz is a small commune in the Manche department of northwestern France, situated in the historic Normandy region.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc8aa1a881909879a694496f11a5 completed April 2, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a0034ec8190bd0a2a368441e44f completed April 5, 2026, 5:21 p.m.
Created at: March 30, 2026, 8:51 p.m.