Triple

T14690574
Position Surface form Disambiguated ID Type / Status
Subject Niigata Prefecture E345022 entity
Predicate containsCity P294 FINISHED
Object Shibata
Shibata is a city in northern Japan known for its historic castle, hot springs, and scenic rural landscapes within Niigata Prefecture.
E1141042 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: Shibata | Statement: [Niigata Prefecture, containsCity, Shibata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shibata
Context triple: [Niigata Prefecture, containsCity, Shibata]
  • A. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • B. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • C. Ishibashi
    Ishibashi is a Japanese surname associated with various notable families and individuals in Japan.
  • D. Tateishi
    Tateishi is a neighborhood in Tokyo known for its traditional shitamachi atmosphere, narrow shopping streets, and old-style bars and eateries.
  • E. Itagaki
    Itagaki is a Japanese surname associated with several notable historical and contemporary figures in Japan.
  • 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: Shibata
Triple: [Niigata Prefecture, containsCity, Shibata]
Generated description
Shibata is a city in northern Japan known for its historic castle, hot springs, and scenic rural landscapes within Niigata Prefecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shibata
Target entity description: Shibata is a city in northern Japan known for its historic castle, hot springs, and scenic rural landscapes within Niigata Prefecture.
  • A. Kiyokawa
    Kiyokawa is a small rural village in Kanagawa Prefecture, Japan, known for its mountainous scenery and outdoor recreation.
  • B. Takaishi
    Takaishi is a city in Osaka Prefecture, Japan, known as a small industrial and residential hub within the Osaka metropolitan area.
  • C. Ishibashi
    Ishibashi is a Japanese surname associated with various notable families and individuals in Japan.
  • D. Tateishi
    Tateishi is a neighborhood in Tokyo known for its traditional shitamachi atmosphere, narrow shopping streets, and old-style bars and eateries.
  • E. Itagaki
    Itagaki is a Japanese surname associated with several notable historical and contemporary figures in Japan.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb585d46c81908d6964130914cec4 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec86ea50c819083d0bbed4c459041 completed May 9, 2026, 5:38 a.m.
NEDg Description generation batch_69fec9b5dc18819087d088e094c3c7b4 completed May 9, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69feca0d38088190910dbf4f2538a9d4 completed May 9, 2026, 5:45 a.m.
Created at: April 10, 2026, 1:28 a.m.