Triple

T32468665
Position Surface form Disambiguated ID Type / Status
Subject Hakkoda Mountains E829783 entity
Predicate hasPeak P8205 FINISHED
Object Mount Kushigamine
Mount Kushigamine is one of the notable peaks within Japan’s Hakkoda Mountains range in Aomori Prefecture.
E2123560 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: Mount Kushigamine | Statement: [Hakkoda Mountains, hasPeak, Mount Kushigamine]
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: Mount Kushigamine
Triple: [Hakkoda Mountains, hasPeak, Mount Kushigamine]
Generated description
Mount Kushigamine is one of the notable peaks within Japan’s Hakkoda Mountains range in Aomori Prefecture.

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_69f3491ee87c81908cbf5890079c2af6 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c35400148190952f711f098ae7a3 completed May 3, 2026, 3:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37c610ef1c8190a7595df1e2c675e5 completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c6cd2c6c81908b0259556d3da946 completed June 21, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_6a37c75384a081909fe2398e87ba9186 completed June 21, 2026, 11:13 a.m.
Created at: May 1, 2026, 12:57 a.m.