Triple

T21095737
Position Surface form Disambiguated ID Type / Status
Subject Waterloo Road E519760 entity
Predicate hasMainCharacter P1183 FINISHED
Object Chlo Grainger 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: Chlo Grainger | Statement: [Waterloo Road, hasMainCharacter, Chlo Grainger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chlo Grainger
Context triple: [Waterloo Road, hasMainCharacter, Chlo Grainger]
  • A. Ellie Grainger
    Ellie Grainger is an actress best known for her role in the critically acclaimed horror film "The Witch."
  • B. Nick Glennie-Smith
    Nick Glennie-Smith is a British film composer and conductor known for his work on high-profile action and adventure movie scores.
  • C. Amelia Hewitt
    Amelia Hewitt was a member of the prominent Hewitt family of New York, known primarily as a daughter of industrialist and politician Abram Stevens Hewitt.
  • D. Holliday Grainger chosen
    Holliday Grainger is an English actress known for her work in film and television, including prominent roles in series like "Patrick Melrose" and "The Borgias" and films such as "Cinderella."
  • E. Cosima Shaw
    Cosima Shaw is a German-British actress known for her work in science fiction and drama, including prominent roles in television and film.
  • 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_69e0b508d8dc81909be940dafe36c8f7 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e71b5845f88190a16f3df157f0906c completed April 21, 2026, 6:38 a.m.
Created at: April 16, 2026, 2:52 p.m.