Triple

T23738285
Position Surface form Disambiguated ID Type / Status
Subject Bra, Piedmont, Italy E586593 entity
Predicate hasReligiousBuilding P1191 FINISHED
Object San Giovanni Battista, Bra
San Giovanni Battista, Bra is a Catholic church in the town of Bra in Italy’s Piedmont region, notable for serving as a historic parish and architectural landmark in the area.
E1602616 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: San Giovanni Battista, Bra | Statement: [Bra, Piedmont, Italy, hasReligiousBuilding, San Giovanni Battista, Bra]
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: San Giovanni Battista, Bra
Triple: [Bra, Piedmont, Italy, hasReligiousBuilding, San Giovanni Battista, Bra]
Generated description
San Giovanni Battista, Bra is a Catholic church in the town of Bra in Italy’s Piedmont region, notable for serving as a historic parish and architectural landmark in the area.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad356c88190ae29ce403145ee73 completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f53cb76148190be086398d09ca4cc completed May 21, 2026, 6:49 p.m.
NEDg Description generation batch_6a0f58183454819094b938a6809c513a completed May 21, 2026, 7:08 p.m.
NED2 Entity disambiguation (via description) batch_6a0f58be2c44819085064c63d07e6906 completed May 21, 2026, 7:10 p.m.
Created at: April 17, 2026, 7:11 p.m.