Triple

T35749112
Position Surface form Disambiguated ID Type / Status
Subject La Bouille E1033267 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object parish church of Saint-Michel
The parish church of Saint-Michel is a historic Catholic church dedicated to Saint Michael, serving as the main place of worship for the local community in La Bouille, France.
E2153669 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: parish church of Saint-Michel | Statement: [La Bouille, hasReligiousBuilding, parish church of Saint-Michel]
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: parish church of Saint-Michel
Triple: [La Bouille, hasReligiousBuilding, parish church of Saint-Michel]
Generated description
The parish church of Saint-Michel is a historic Catholic church dedicated to Saint Michael, serving as the main place of worship for the local community in La Bouille, France.

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_69f76e119d508190a3873cb302063832 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7a1961d7c819087a12d0f71be150f completed May 3, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387d2b2a688190861708c061f795dc completed June 22, 2026, 12:09 a.m.
NEDg Description generation batch_6a387e0b606c819093d074bde21518d2 completed June 22, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_6a3880fb52d4819099c2bdba7e7d948f completed June 22, 2026, 12:25 a.m.
Created at: May 3, 2026, 4:06 p.m.