Triple

T8354608
Position Surface form Disambiguated ID Type / Status
Subject Mount Ontake E196652 entity
Predicate nearbyCity P350 FINISHED
Object Gero
Gero is a Japanese hot spring resort city in Gifu Prefecture, renowned for its historic onsen baths and scenic mountain surroundings.
E727569 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: Gero | Statement: [Mount Ontake, nearbyCity, Gero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gero
Context triple: [Mount Ontake, nearbyCity, Gero]
  • A. Gerenia
    Gerenia is an ancient town in Messenia, Greece, best known in Greek mythology as the homeland of the wise hero Nestor.
  • B. Geras
    Geras is the Greek personification of old age, often depicted as a withered, decrepit figure and associated with the inevitable decline that comes with time.
  • C. Geri
    Geri is a common diminutive or nickname for the given name Geraldine.
  • D. Geri
    Geri is one of the two mythological wolves who accompany the Norse god Odin.
  • E. Gerson
    Gerson is a surname most notably associated with American screenwriter Daniel Gerson, known for co-writing several popular animated films.
  • 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: Gero
Triple: [Mount Ontake, nearbyCity, Gero]
Generated description
Gero is a Japanese hot spring resort city in Gifu Prefecture, renowned for its historic onsen baths and scenic mountain surroundings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gero
Target entity description: Gero is a Japanese hot spring resort city in Gifu Prefecture, renowned for its historic onsen baths and scenic mountain surroundings.
  • A. Gerenia
    Gerenia is an ancient town in Messenia, Greece, best known in Greek mythology as the homeland of the wise hero Nestor.
  • B. Geras
    Geras is the Greek personification of old age, often depicted as a withered, decrepit figure and associated with the inevitable decline that comes with time.
  • C. Geri
    Geri is a common diminutive or nickname for the given name Geraldine.
  • D. Geri
    Geri is one of the two mythological wolves who accompany the Norse god Odin.
  • E. Gerson
    Gerson is a surname most notably associated with American screenwriter Daniel Gerson, known for co-writing several popular animated films.
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb8048edb88190a1980ad74818b898 completed March 31, 2026, 8:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc75e94288190ba1905dd4ca172dd completed April 2, 2026, 1:33 a.m.
NEDg Description generation batch_69cdcc86626c8190a4206feedea24b41 completed April 2, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69cdcde02e088190be8220f7d18d6700 completed April 2, 2026, 2:01 a.m.
Created at: March 30, 2026, 5:59 p.m.