Triple

T25338154
Position Surface form Disambiguated ID Type / Status
Subject Garth railway station E635332 entity
Predicate serviceOperator P5884 FINISHED
Object Transport for Wales E10845 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: Transport for Wales | Statement: [Garth railway station, serviceOperator, Transport for Wales]

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_69e75a99bd6481909476115b35b9a8e4 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f498b4cbb88190a8ac563ad1a73b5d completed May 1, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10897bae988190b902cfef58376358 completed May 22, 2026, 4:51 p.m.
Created at: April 21, 2026, 1:32 p.m.