Triple

T16617129
Position Surface form Disambiguated ID Type / Status
Subject Félibrige movement E403723 entity
Predicate foundedBy P104 FINISHED
Object Anselme Mathieu
Anselme Mathieu was a 19th-century Provençal poet and winemaker who was one of the founding members of the Félibrige movement dedicated to reviving the Occitan language and literature.
E1908412 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: Anselme Mathieu | Statement: [Félibrige movement, foundedBy, Anselme Mathieu]
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: Anselme Mathieu
Triple: [Félibrige movement, foundedBy, Anselme Mathieu]
Generated description
Anselme Mathieu was a 19th-century Provençal poet and winemaker who was one of the founding members of the Félibrige movement dedicated to reviving the Occitan language and literature.

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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754ac9dc8190965197024594742b completed April 18, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ec9d3c481909ebe21b86418eb0d completed June 9, 2026, 1:39 a.m.
NEDg Description generation batch_6a27700902c88190b2ccb53c4bce92d3 completed June 9, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a2770b9c5148190834f1748388200a2 completed June 9, 2026, 1:47 a.m.
Created at: April 10, 2026, 5:17 a.m.