Triple

T36900266
Position Surface form Disambiguated ID Type / Status
Subject Església de Sant Corneli i Sant Cebrià d’Ordino E912012 entity
Predicate locatedIn P40 FINISHED
Object Parròquia d’Ordino
Parròquia d’Ordino is a parish in the northern part of Andorra known for its traditional villages, Romanesque heritage, and mountainous landscapes.
E2205157 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: Parròquia d’Ordino | Statement: [Església de Sant Corneli i Sant Cebrià d’Ordino, locatedIn, Parròquia d’Ordino]
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: Parròquia d’Ordino
Triple: [Església de Sant Corneli i Sant Cebrià d’Ordino, locatedIn, Parròquia d’Ordino]
Generated description
Parròquia d’Ordino is a parish in the northern part of Andorra known for its traditional villages, Romanesque heritage, and mountainous landscapes.

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_69f76e841b54819097e7fa768bbc70b2 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fd933a488190a99dd4af4f148a20 completed May 5, 2026, 2:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e1623c2d48190a03864bb0a67305e completed June 26, 2026, 6:03 a.m.
NEDg Description generation batch_6a3e16c7ae008190aed858fd5da64a5d completed June 26, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a3e2225d4fc8190baaf1e61f7e1642f completed June 26, 2026, 6:54 a.m.
Created at: May 3, 2026, 4:13 p.m.