Triple

T24117409
Position Surface form Disambiguated ID Type / Status
Subject Emmanuel Frémiet E597555 entity
Predicate burialPlace P196 FINISHED
Object Cimetière de Louveciennes
Cimetière de Louveciennes is a cemetery in Louveciennes, France, known as the final resting place of several notable figures, including sculptor Emmanuel Frémiet.
E1617482 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: Cimetière de Louveciennes | Statement: [Emmanuel Frémiet, burialPlace, Cimetière de Louveciennes]
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: Cimetière de Louveciennes
Triple: [Emmanuel Frémiet, burialPlace, Cimetière de Louveciennes]
Generated description
Cimetière de Louveciennes is a cemetery in Louveciennes, France, known as the final resting place of several notable figures, including sculptor Emmanuel Frémiet.

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_69e288c74200819098ab875b592cb39f completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1dedf824081908de34db4ced62c13 completed April 29, 2026, 10:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f968e05e88190b9579b5c25d7a09c completed May 21, 2026, 11:34 p.m.
NEDg Description generation batch_6a0f982bbdf881909c1651b1d2a91c85 completed May 21, 2026, 11:41 p.m.
NED2 Entity disambiguation (via description) batch_6a0f99ae95f88190b09d6ad00f85290d completed May 21, 2026, 11:47 p.m.
Created at: April 17, 2026, 11:04 p.m.