Triple

T33012696
Position Surface form Disambiguated ID Type / Status
Subject Terranjou E844686 entity
Predicate formedByMergerOf P77 FINISHED
Object Chavagnes
Chavagnes is a former French commune in the Maine-et-Loire department that was incorporated into the new commune of Terranjou.
E2072506 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: Chavagnes | Statement: [Terranjou, formedByMergerOf, Chavagnes]
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: Chavagnes
Triple: [Terranjou, formedByMergerOf, Chavagnes]
Generated description
Chavagnes is a former French commune in the Maine-et-Loire department that was incorporated into the new commune of Terranjou.

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_69f3494f3b4081909dccf2af34372a26 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d2a85ad481908335652bd38873fb completed May 3, 2026, 4:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36821bf67c8190af49c3a3c4723930 completed June 20, 2026, 12:05 p.m.
NEDg Description generation batch_6a3682cb71688190a91c1b9ecba2c37f completed June 20, 2026, 12:08 p.m.
NED2 Entity disambiguation (via description) batch_6a368327e7248190801ee93ba760d704 completed June 20, 2026, 12:10 p.m.
Created at: May 1, 2026, 1:23 a.m.