Triple

T37122965
Position Surface form Disambiguated ID Type / Status
Subject Gouvy railway station E919311 entity
Predicate connectsTo P845 FINISHED
Object Liège E142916 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: Liège | Statement: [Gouvy railway station, connectsTo, Liège]

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_69f76e9c57148190ba789dd059645bb9 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb3037a44881909be700728d720c1e completed May 6, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406370e36c819093e5d6d2b0a1a6c2 completed June 27, 2026, 11:57 p.m.
Created at: May 3, 2026, 4:15 p.m.