Triple

T1135513
Position Surface form Disambiguated ID Type / Status
Subject Hyogo Prefecture E23129 entity
Predicate hasCity P316 FINISHED
Object Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
 E151720 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: Shiso | Statement: [Hyogo Prefecture, hasCity, Shiso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shiso
Context triple: [Hyogo Prefecture, hasCity, Shiso]
  • A. Taro
    Taro is a common Japanese male given name, often written with kanji meaning "eldest son" or similar traditional connotations.
  • B. Maki
    Maki is a Japanese surname most notably associated with Fumihiko Maki, a prominent modernist architect known for his innovative urban and architectural designs.
  • C. Sasazuka
    Sasazuka is a residential and commercial neighborhood in Tokyo known for its convenient access to central Shibuya and its mix of traditional shopping streets and modern urban living.
  • D. Anogi
    Anogi is a small traditional mountain village on the Greek island of Ithaca, known for its historic church, stone houses, and panoramic views.
  • E. Tamada
    Tamada is the traditional Georgian toastmaster who leads feasts and orchestrates toasts during the supra, Georgia’s ceremonial banquet.
  • 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: Shiso
Triple: [Hyogo Prefecture, hasCity, Shiso]
Generated description
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shiso
Target entity description: Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
  • A. Taro
    Taro is a common Japanese male given name, often written with kanji meaning "eldest son" or similar traditional connotations.
  • B. Maki
    Maki is a Japanese surname most notably associated with Fumihiko Maki, a prominent modernist architect known for his innovative urban and architectural designs.
  • C. Sasazuka
    Sasazuka is a residential and commercial neighborhood in Tokyo known for its convenient access to central Shibuya and its mix of traditional shopping streets and modern urban living.
  • D. Anogi
    Anogi is a small traditional mountain village on the Greek island of Ithaca, known for its historic church, stone houses, and panoramic views.
  • E. Tamada
    Tamada is the traditional Georgian toastmaster who leads feasts and orchestrates toasts during the supra, Georgia’s ceremonial banquet.
  • 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_69a493ec75988190b63a11bafaec29b4 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc2300c481908c60fbb1188c37c5 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf13304881908aa74d92ef7b1c86 completed March 8, 2026, 12:13 a.m.
NEDg Description generation batch_69acbf873544819099d3dff98a6b2244 completed March 8, 2026, 12:15 a.m.
NED2 Entity disambiguation (via description) batch_69acc06483b08190b5b29f684b83f43f completed March 8, 2026, 12:18 a.m.
Created at: March 1, 2026, 7:44 p.m.