Triple

T30318370
Position Surface form Disambiguated ID Type / Status
Subject Cinq grandes odes E771118 entity
Predicate hasPart P35 FINISHED
Object La Vierge à midi
La Vierge à midi is a lyrical poem by Paul Claudel that offers a contemplative meditation on the Virgin Mary at midday, blending religious devotion with rich symbolic imagery.
E1907677 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: La Vierge à midi | Statement: [Cinq grandes odes, hasPart, La Vierge à midi]
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: La Vierge à midi
Triple: [Cinq grandes odes, hasPart, La Vierge à midi]
Generated description
La Vierge à midi is a lyrical poem by Paul Claudel that offers a contemplative meditation on the Virgin Mary at midday, blending religious devotion with rich symbolic imagery.

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_69f22489ee8481909344649bfbb92e83 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68195fcfc8190b6d3ee313c734f60 completed May 2, 2026, 10:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276f1679b08190b394bf9aefe654c1 completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a276fa88d248190a7bc70990a19ba5a completed June 9, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a277064150c8190a1d43e89ec3c4886 completed June 9, 2026, 1:46 a.m.
Created at: April 29, 2026, 7:51 p.m.