Triple

T35266185
Position Surface form Disambiguated ID Type / Status
Subject Ogimachi E1018521 entity
Predicate hasBuilding P105 FINISHED
Object Nagase House
Nagase House is a historic gassho-zukuri farmhouse in the preserved village of Ogimachi in Shirakawa-go, Japan, known for its steep thatched roof and traditional rural architecture.
E2135733 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: Nagase House | Statement: [Ogimachi, hasBuilding, Nagase House]
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: Nagase House
Triple: [Ogimachi, hasBuilding, Nagase House]
Generated description
Nagase House is a historic gassho-zukuri farmhouse in the preserved village of Ogimachi in Shirakawa-go, Japan, known for its steep thatched roof and traditional rural 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_69f76de4be5c8190a51705c07612cac8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78f9a095881908d7d5d1914afae77 completed May 3, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3819d706a08190b2b7e87d83107784 completed June 21, 2026, 5:05 p.m.
NEDg Description generation batch_6a381b16bb748190ad9ff7c8683dbf96 completed June 21, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a381f0ac04c81908d5630d9b3f7308f completed June 21, 2026, 5:27 p.m.
Created at: May 3, 2026, 4:02 p.m.