Triple

T26516540
Position Surface form Disambiguated ID Type / Status
Subject Isabelle Carré E669826 entity
Predicate notableWork P4 FINISHED
Object La Chambre des officiers
La Chambre des officiers is a French drama film adaptation of Marc Dugain’s novel about a World War I officer disfigured in combat, in which Isabelle Carré plays a prominent role.
E1729888 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: La Chambre des officiers | Statement: [Isabelle Carré, notableWork, La Chambre des officiers]
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: La Chambre des officiers
Triple: [Isabelle Carré, notableWork, La Chambre des officiers]
Generated description
La Chambre des officiers is a French drama film adaptation of Marc Dugain’s novel about a World War I officer disfigured in combat, in which Isabelle Carré plays a prominent role.

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_69eeb31b6dcc8190b30632dc3928a0c0 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613bd3f308190a936e670bf8a1b4e completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11bb418f0c819087d0da0e73237015 completed May 23, 2026, 2:35 p.m.
NEDg Description generation batch_6a11be62602081909cac24dd194530b4 completed May 23, 2026, 2:49 p.m.
NED2 Entity disambiguation (via description) batch_6a11bee7bd508190a8d6a18cf0a238a1 completed May 23, 2026, 2:51 p.m.
Created at: April 27, 2026, 1:24 a.m.