Triple

T4932489
Position Surface form Disambiguated ID Type / Status
Subject Mount Tanigawa E110728 entity
Predicate hasSummitName P17095 FINISHED
Object Toma-no-mimi
Toma-no-mimi is one of the twin main peaks forming the summit area of Mount Tanigawa in Japan’s Tanigawa mountain range.
 E482762 NE FINISHED

How this triple was built (4 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: Toma-no-mimi | Statement: [Mount Tanigawa, hasSummitName, Toma-no-mimi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Toma-no-mimi
Context triple: [Mount Tanigawa, hasSummitName, Toma-no-mimi]
  • A. Chimariko
    Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
  • B. Yodo-dono
    Yodo-dono was a prominent Japanese noblewoman and political figure of the late Sengoku period, best known as Toyotomi Hideyoshi’s consort and the mother of his heir, Toyotomi Hideyori.
  • C. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • D. Shimotsuki
    Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
  • E. Munefusa
    Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Toma-no-mimi
Triple: [Mount Tanigawa, hasSummitName, Toma-no-mimi]
Generated description
Toma-no-mimi is one of the twin main peaks forming the summit area of Mount Tanigawa in Japan’s Tanigawa mountain range.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Toma-no-mimi
Target entity description: Toma-no-mimi is one of the twin main peaks forming the summit area of Mount Tanigawa in Japan’s Tanigawa mountain range.
  • A. Chimariko
    Chimariko is an extinct Native American language once spoken by the Chimariko people in northwestern California.
  • B. Yodo-dono
    Yodo-dono was a prominent Japanese noblewoman and political figure of the late Sengoku period, best known as Toyotomi Hideyoshi’s consort and the mother of his heir, Toyotomi Hideyori.
  • C. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • D. Shimotsuki
    Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
  • E. Munefusa
    Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
  • F. None of above. chosen

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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7063c57c8190a5a6fb3586238d35 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81c5f8ec8190834c624bae17adff completed March 21, 2026, 11:32 a.m.
NEDg Description generation batch_69be845a59a881909d69ea10d0563b5a completed March 21, 2026, 11:43 a.m.
NED2 Entity disambiguation (via description) batch_69be84ea51288190bb72fd95a7e4f9d4 completed March 21, 2026, 11:45 a.m.
Created at: March 20, 2026, 1:30 p.m.