Triple

T24048341
Position Surface form Disambiguated ID Type / Status
Subject EURODUAL E595583 entity
Predicate manufacturer P490 FINISHED
Object Stadler Rail E146008 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: Stadler Rail | Statement: [EURODUAL, manufacturer, Stadler Rail]

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_69e288c06a908190899cad4531f32c9a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d9cedaa08190bf54857de1b312ed completed April 29, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10759fb6bc8190a5f1c2ec2f2dca6a completed May 22, 2026, 3:26 p.m.
Created at: April 17, 2026, 10:18 p.m.