Triple

T5531648
Position Surface form Disambiguated ID Type / Status
Subject Damage (1992 film) E145061 entity
Predicate supportingActorRole P44204 FINISHED
Object Rupert Graves as Martyn Fleming LITERAL FINISHED

How this triple was built (1 step)

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: Rupert Graves as Martyn Fleming | Statement: [Damage (1992 film), supportingActorRole, Rupert Graves as Martyn Fleming]

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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f9d17ec8190b93b12931a4c1b33 completed March 22, 2026, 4:58 p.m.
Created at: March 22, 2026, 3:34 p.m.