Triple

T26915274
Position Surface form Disambiguated ID Type / Status
Subject La Pléiade E677500 entity
Predicate member P10 FINISHED
Object Pontus de Tyard
Pontus de Tyard was a 16th-century French poet, humanist, and cleric associated with the Renaissance literary movement La Pléiade.
E1746273 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: Pontus de Tyard | Statement: [La Pléiade, member, Pontus de Tyard]
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: Pontus de Tyard
Triple: [La Pléiade, member, Pontus de Tyard]
Generated description
Pontus de Tyard was a 16th-century French poet, humanist, and cleric associated with the Renaissance literary movement La Pléiade.

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_69eee9bcef1c8190be88586bb902bb9b completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61fdd39ec8190aaf1714330459136 completed May 2, 2026, 4:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a121eb4f5208190939fe86ba18a47ab completed May 23, 2026, 9:40 p.m.
NEDg Description generation batch_6a121f5c372481909cfd4c5ebc39f5ea completed May 23, 2026, 9:42 p.m.
NED2 Entity disambiguation (via description) batch_6a122004aadc819084dbaa834408a0bc completed May 23, 2026, 9:45 p.m.
Created at: April 27, 2026, 6:04 a.m.