Triple

T27047693
Position Surface form Disambiguated ID Type / Status
Subject Darius Milhaud E684685 entity
Predicate spouse P13 FINISHED
Object Madeleine Milhaud
Madeleine Milhaud was a French actress, librettist, and writer closely associated with 20th-century French music and theatre.
 E684685 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: Madeleine Milhaud | Statement: [Darius Milhaud, spouse, Madeleine Milhaud]
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: Madeleine Milhaud
Triple: [Darius Milhaud, spouse, Madeleine Milhaud]
Generated description
Madeleine Milhaud was a French actress, librettist, and writer closely associated with 20th-century French music and theatre.

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_69ef148193c48190bb1a0cfae6a407c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f622acea248190a90c685058f42184 completed May 2, 2026, 4:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247f5ce48819096dba2919e2b7901 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a1248e698008190b4e1d77080b52fef completed May 24, 2026, 12:40 a.m.
NED2 Entity disambiguation (via description) batch_6a1249ea67c8819092a4905943bd6e0e completed May 24, 2026, 12:44 a.m.
Created at: April 27, 2026, 8:11 a.m.