Triple

T23801477
Position Surface form Disambiguated ID Type / Status
Subject Moulin E588684 entity
Predicate hasNotableBearer P458 FINISHED
Object Denis Moulin
Denis Moulin is an individual notable enough to be recognized as a bearer of the surname Moulin, though specific widely known public details about him are not readily available.
E1756033 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: Denis Moulin | Statement: [Moulin, hasNotableBearer, Denis Moulin]
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: Denis Moulin
Triple: [Moulin, hasNotableBearer, Denis Moulin]
Generated description
Denis Moulin is an individual notable enough to be recognized as a bearer of the surname Moulin, though specific widely known public details about him are not readily available.

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_69e25d15db58819092ac1e6791696fd9 completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c74e430481909debd10c71785912 completed April 29, 2026, 8:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1247c94bc48190af7b969991842c60 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a12488822208190aab1355ac3efd2a6 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124935c01c8190b9d6d13c4f50a104 completed May 24, 2026, 12:41 a.m.
Created at: April 17, 2026, 7:53 p.m.