Triple

T34960798
Position Surface form Disambiguated ID Type / Status
Subject Hank Cosby E1008247 entity
Predicate employer P7 FINISHED
Object Motown Records E9139 NE 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: Motown Records | Statement: [Hank Cosby, employer, Motown Records]

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_69f76dc69564819099e9e78aed6ff0a6 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78421f9c481909caf6db43f3d943a completed May 3, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b26bd6ec81909adc57d5fd12b109 completed June 21, 2026, 9:44 a.m.
Created at: May 3, 2026, 4 p.m.