Triple

T37004989
Position Surface form Disambiguated ID Type / Status
Subject Mount Hakuba Norikura E915765 entity
Predicate near P350 FINISHED
Object Hakuba village
Hakuba village is a popular mountain resort area in Japan’s Northern Alps, renowned for its ski slopes, hiking trails, and role as a venue during the 1998 Nagano Winter Olympics.
E248799 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: Hakuba village | Statement: [Mount Hakuba Norikura, near, Hakuba village]
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: Hakuba village
Triple: [Mount Hakuba Norikura, near, Hakuba village]
Generated description
Hakuba village is a popular mountain resort area in Japan’s Northern Alps, renowned for its ski slopes, hiking trails, and role as a venue during the 1998 Nagano Winter Olympics.

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_69f76e90ed548190b187d2475f5c807d completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa0029fe9c8190b7d4df83ab26b669 completed May 5, 2026, 2:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043a677f4819089bae352bdf54f9a completed June 27, 2026, 9:41 p.m.
NEDg Description generation batch_6a40443a34148190b5b0848559466617 completed June 27, 2026, 9:44 p.m.
NED2 Entity disambiguation (via description) batch_6a404639e5a88190a204ac46e57a660f completed June 27, 2026, 9:52 p.m.
Created at: May 3, 2026, 4:14 p.m.