Triple

T27520016
Position Surface form Disambiguated ID Type / Status
Subject Festival International des Cinémas d’Asie de Vesoul E694681 entity
Predicate foundedBy P104 FINISHED
Object Martine Thérouanne
Martine Thérouanne is a French cultural organizer best known as a co-founder and driving force behind the Vesoul International Festival of Asian Cinema.
E1929192 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: Martine Thérouanne | Statement: [Festival International des Cinémas d’Asie de Vesoul, foundedBy, Martine Thérouanne]
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: Martine Thérouanne
Triple: [Festival International des Cinémas d’Asie de Vesoul, foundedBy, Martine Thérouanne]
Generated description
Martine Thérouanne is a French cultural organizer best known as a co-founder and driving force behind the Vesoul International Festival of Asian Cinema.

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_69ef538550208190aa9de8e2cb260d93 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f2accf081908b50f8473deda2de completed May 2, 2026, 5:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2898b1eba08190bc56ed497031ee33 completed June 9, 2026, 10:50 p.m.
NEDg Description generation batch_6a289970128c8190a8a5d8f04db9a9c1 completed June 9, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a289a90fec48190a132ca1f6a9db98b completed June 9, 2026, 10:58 p.m.
Created at: April 27, 2026, 1:20 p.m.