Triple

T37672487
Position Surface form Disambiguated ID Type / Status
Subject Shugakuin Imperial Villa E937999 entity
Predicate hasComponent P35 FINISHED
Object Lower Villa
Lower Villa is one of the three main garden and residence complexes within Kyoto’s Shugakuin Imperial Villa, known for its traditional Japanese landscape design and imperial architecture.
E2239568 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: Lower Villa | Statement: [Shugakuin Imperial Villa, hasComponent, Lower Villa]
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: Lower Villa
Triple: [Shugakuin Imperial Villa, hasComponent, Lower Villa]
Generated description
Lower Villa is one of the three main garden and residence complexes within Kyoto’s Shugakuin Imperial Villa, known for its traditional Japanese landscape design and imperial architecture.

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_69f76ed7b1408190ba8c93c53cb8becf completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fba9e6be1c8190ad03baea7b8d76d0 completed May 6, 2026, 8:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40cdb54b0c8190ad27ed4033960245 completed June 28, 2026, 7:31 a.m.
NEDg Description generation batch_6a40ce5899208190bd9ce55470abe0e7 completed June 28, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_6a40cf3590c48190988529eb57a92a9e completed June 28, 2026, 7:37 a.m.
Created at: May 3, 2026, 4:18 p.m.