Triple

T30224175
Position Surface form Disambiguated ID Type / Status
Subject Euskalduna Conference Centre E768431 entity
Predicate namedAfter P63 FINISHED
Object Euskalduna shipyard
Euskalduna shipyard was a major former shipbuilding facility in Bilbao, Spain, whose legacy is commemorated by the Euskalduna Conference Centre built on its former site.
E1906430 NE FINISHED

How this triple was built (2 steps)

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: Euskalduna shipyard | Statement: [Euskalduna Conference Centre, namedAfter, Euskalduna shipyard]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Euskalduna shipyard
Triple: [Euskalduna Conference Centre, namedAfter, Euskalduna shipyard]
Generated description
Euskalduna shipyard was a major former shipbuilding facility in Bilbao, Spain, whose legacy is commemorated by the Euskalduna Conference Centre built on its former site.

Provenance (5 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_69f2248108208190be60bf1af343ce70 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68020c22c8190915c9d990116469f completed May 2, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276440be9081909a80cd3699d7a613 completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2764f2c6588190b88039903b3d891c completed June 9, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a27660e070081909f126b4b0e6cb63b completed June 9, 2026, 1:02 a.m.
Created at: April 29, 2026, 7:35 p.m.