Triple

T32907976
Position Surface form Disambiguated ID Type / Status
Subject Yerres E841792 entity
Predicate hasPark P105 FINISHED
Object Parc Caillebotte
Parc Caillebotte is a historic landscaped park in Yerres, France, best known for surrounding the former estate of Impressionist painter Gustave Caillebotte and featuring picturesque gardens, waterways, and walking paths.
E2028490 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: Parc Caillebotte | Statement: [Yerres, hasPark, Parc Caillebotte]
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: Parc Caillebotte
Triple: [Yerres, hasPark, Parc Caillebotte]
Generated description
Parc Caillebotte is a historic landscaped park in Yerres, France, best known for surrounding the former estate of Impressionist painter Gustave Caillebotte and featuring picturesque gardens, waterways, and walking paths.

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_69f34946a5208190bbd79f0fec4323bd completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d09bd85c819086ad33680c3eae49 completed May 3, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34c69707bc8190a396eefd2adaead0 completed June 19, 2026, 4:33 a.m.
NEDg Description generation batch_6a34c85cab748190abd850dca56c39ac completed June 19, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_6a34c9336fc4819092f2682493a94cfe completed June 19, 2026, 4:44 a.m.
Created at: May 1, 2026, 1:19 a.m.