Triple

T22604399
Position Surface form Disambiguated ID Type / Status
Subject La loi du marché E574916 entity
Predicate mainCharacter P1183 FINISHED
Object Thierry Taugourdeau
Thierry Taugourdeau is the middle-aged, working-class protagonist of the French social drama film "La loi du marché" ("The Measure of a Man"), who struggles with unemployment and moral dilemmas in contemporary France.
E1755921 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: Thierry Taugourdeau | Statement: [La loi du marché, mainCharacter, Thierry Taugourdeau]
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: Thierry Taugourdeau
Triple: [La loi du marché, mainCharacter, Thierry Taugourdeau]
Generated description
Thierry Taugourdeau is the middle-aged, working-class protagonist of the French social drama film "La loi du marché" ("The Measure of a Man"), who struggles with unemployment and moral dilemmas in contemporary 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1626fad6881909895cc8c0af62f0d completed April 29, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1247c6f6cc8190ad5c32aa57f7b78d completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a12489d7498819083fb008e2acff886 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124918ab688190b6172f571d3aba73 completed May 24, 2026, 12:40 a.m.
Created at: April 17, 2026, 2:51 p.m.