Triple

T24860464
Position Surface form Disambiguated ID Type / Status
Subject Lydia Davis E622136 entity
Predicate notableAuthorTranslated P141041 FINISHED
Object Pierre Jean Jouve
Pierre Jean Jouve was a French poet and novelist known for his psychologically intense, often spiritually and erotically charged works that bridged Symbolism and modernism.
E2289928 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: Pierre Jean Jouve | Statement: [Lydia Davis, notableAuthorTranslated, Pierre Jean Jouve]
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: Pierre Jean Jouve
Triple: [Lydia Davis, notableAuthorTranslated, Pierre Jean Jouve]
Generated description
Pierre Jean Jouve was a French poet and novelist known for his psychologically intense, often spiritually and erotically charged works that bridged Symbolism and modernism.

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_69e2fac350d08190b3affde1b451a8c5 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f6b3ad0d0481909f2cf7d931a3a418 completed May 3, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5b7eca7db481909334fa26c1ca20a6 completed July 18, 2026, 1:25 p.m.
NEDg Description generation batch_6a5b7f3fca34819094c8bc80af4243e5 completed July 18, 2026, 1:27 p.m.
NED2 Entity disambiguation (via description) batch_6a5b7f95cff081909a1c308ce062ccc0 completed July 18, 2026, 1:28 p.m.
Created at: April 18, 2026, 5:22 a.m.