Triple

T9754633
Position Surface form Disambiguated ID Type / Status
Subject Elissa Knight E236522 entity
Predicate characterIn P12208 FINISHED
Object Cars E46398 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: Cars | Statement: [Elissa Knight, characterIn, Cars]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cars
Context triple: [Elissa Knight, characterIn, Cars]
  • A. Cars chosen
    Cars is a 2006 Pixar animated film that follows a hotshot race car who discovers friendship and humility in a forgotten desert town.
  • B. CAR
    CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
  • C. CAR
    CAR is the Cordillera Administrative Region in the Philippines, an upland area in Northern Luzon known for its mountainous terrain and indigenous cultures.
  • D. CAR
    CAR is the National Rail station code for Carlisle railway station in Cumbria, England.
  • E. CAR
    CAR is the acronym commonly used for the Council for Aboriginal Reconciliation, an Australian body established to promote understanding and improved relations between Aboriginal and Torres Strait Islander peoples and the wider community.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9fb01ad08190b2435fa505c622bc completed April 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d32a5921c8819085a2188805b4811c completed April 6, 2026, 3:36 a.m.
Created at: March 30, 2026, 8:24 p.m.