Triple

T24368544
Position Surface form Disambiguated ID Type / Status
Subject Gerald of Aurillac E614266 entity
Predicate associatedWithPlace P2830 FINISHED
Object Aurillac Abbey
Aurillac Abbey was a prominent medieval Benedictine monastery in Aurillac, France, known as the religious center connected with the noble saint Gerald of Aurillac.
E1648379 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: Aurillac Abbey | Statement: [Gerald of Aurillac, associatedWithPlace, Aurillac Abbey]
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: Aurillac Abbey
Triple: [Gerald of Aurillac, associatedWithPlace, Aurillac Abbey]
Generated description
Aurillac Abbey was a prominent medieval Benedictine monastery in Aurillac, France, known as the religious center connected with the noble saint Gerald of Aurillac.

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_69e2d7e1e010819098b95eb3f905943d completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f2938994c081909730d1e02e823dfd completed April 29, 2026, 11:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a100fd7da488190b404f382f8151f08 completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a10136871588190b4e4b4618ab7a400 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10140b2fec8190aa6d805f54926b56 completed May 22, 2026, 8:30 a.m.
Created at: April 18, 2026, 2:01 a.m.