Triple

T24434206
Position Surface form Disambiguated ID Type / Status
Subject Philippe de Villiers E616079 entity
Predicate positionHeld P8 FINISHED
Object Secretary of State for Culture
The Secretary of State for Culture is a French government post responsible for national cultural policy, including the arts, heritage, and cultural institutions.
E1633826 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: Secretary of State for Culture | Statement: [Philippe de Villiers, positionHeld, Secretary of State for Culture]
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: Secretary of State for Culture
Triple: [Philippe de Villiers, positionHeld, Secretary of State for Culture]
Generated description
The Secretary of State for Culture is a French government post responsible for national cultural policy, including the arts, heritage, and cultural institutions.

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_69e2d7ec44b081909ccaf1f3bbec0641 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f297855fd08190904eedd2666d9622 completed April 29, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe37841808190b020f8605ebe54c2 completed May 22, 2026, 5:02 a.m.
NEDg Description generation batch_6a0fe3f19fec81909b7dd2fd9975336e completed May 22, 2026, 5:04 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe46b72b48190b2c0d2d9ddaf3107 completed May 22, 2026, 5:06 a.m.
Created at: April 18, 2026, 2:16 a.m.