Triple

T38334396
Position Surface form Disambiguated ID Type / Status
Subject White Sands E1037911 entity
Predicate plotSummary P264 FINISHED
Object A small-town sheriff discovers a dead body and a suitcase full of cash and becomes entangled in a web of murder, impersonation, and arms dealing. 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: A small-town sheriff discovers a dead body and a suitcase full of cash and becomes entangled in a web of murder, impersonation, and arms dealing. | Statement: [White Sands, plotSummary, A small-town sheriff discovers a dead body and a suitcase full of cash and becomes entangled in a web of murder, impersonation, and arms dealing.]

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_69f76e20d65c81909619ac0dd85c56f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6ba09388190a230366c98fa35da completed May 7, 2026, 5:07 p.m.
Created at: May 3, 2026, 4:30 p.m.