Triple

T23735211
Position Surface form Disambiguated ID Type / Status
Subject Mount Yufu E586522 entity
Predicate hasSummit P8024 FINISHED
Object Higashi-mine
Higashi-mine is one of the twin peaks forming the summit of Mount Yufu, a prominent volcanic mountain in Ōita Prefecture, Japan.
E1618206 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: Higashi-mine | Statement: [Mount Yufu, hasSummit, Higashi-mine]
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: Higashi-mine
Triple: [Mount Yufu, hasSummit, Higashi-mine]
Generated description
Higashi-mine is one of the twin peaks forming the summit of Mount Yufu, a prominent volcanic mountain in Ōita Prefecture, Japan.

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_69e24907dc9c8190be074c9c96a0ec2d completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bad07bd08190b04d7a4c8732a856 completed April 29, 2026, 8:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f962b22908190b966659ff4272139 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f971a0f108190ba6d5b57da2acbdf completed May 21, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_6a0f981441b08190a0076042748d92ea completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 7:10 p.m.