Triple

T4155821
Position Surface form Disambiguated ID Type / Status
Subject Adrien Brody E91411 entity
Predicate occupation P3 FINISHED
Object actor 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: actor | Statement: [Adrien Brody, occupation, actor]

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_69aed9626ebc8190a39de631788bea3e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af028e3e5c8190bc1d5a9b9dff1d14 completed March 9, 2026, 5:25 p.m.
Created at: March 9, 2026, 3:44 p.m.