Triple

T3686125
Position Surface form Disambiguated ID Type / Status
Subject Jun’ya Koizumi E78228 entity
Predicate familyName P18 FINISHED
Object Koizumi E86419 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: Koizumi | Statement: [Jun’ya Koizumi, familyName, Koizumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koizumi
Context triple: [Jun’ya Koizumi, familyName, Koizumi]
  • A. Koizumi chosen
    Koizumi is a Japanese surname most prominently associated with Junichiro Koizumi, a former Prime Minister of Japan known for his reformist policies.
  • B. Nezu
    Nezu is a traditional neighborhood in Tokyo known for its historic Nezu Shrine, old-town atmosphere, and preserved shitamachi streets.
  • C. Kashiba
    Kashiba is a city in Japan known for its residential communities and location in the northwestern part of Nara Prefecture, near the Osaka metropolitan area.
  • D. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • E. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c676748190b074abfb9ba43b49 completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b57f0989c88190b4c675c7a6ec0e3e completed March 14, 2026, 3:30 p.m.
Created at: March 8, 2026, 3:26 p.m.