Triple

T33933627
Position Surface form Disambiguated ID Type / Status
Subject Hakuba 47 Winter Sports Park E869969 entity
Predicate near P350 FINISHED
Object Hakuba Goryu Snow Resort
Hakuba Goryu Snow Resort is a popular ski and snowboard area in Japan’s Hakuba Valley, known for its varied terrain, reliable snow, and connection to neighboring resorts.
E2084184 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 Goryu Snow Resort | Statement: [Hakuba 47 Winter Sports Park, near, Hakuba Goryu Snow Resort]
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 Goryu Snow Resort
Triple: [Hakuba 47 Winter Sports Park, near, Hakuba Goryu Snow Resort]
Generated description
Hakuba Goryu Snow Resort is a popular ski and snowboard area in Japan’s Hakuba Valley, known for its varied terrain, reliable snow, and connection to neighboring resorts.

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_69f3499a59788190bff762a891471b31 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7022a75a881909ea0cc2e6a2fe4a2 completed May 3, 2026, 8:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1af01fc81908ff6d3a5b188240f completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c265a4588190b415159def7d4690 completed June 20, 2026, 4:40 p.m.
NED2 Entity disambiguation (via description) batch_6a36c4cc187081908cd56a998ab5c90d completed June 20, 2026, 4:50 p.m.
Created at: May 1, 2026, 1:49 a.m.