Triple

T905587
Position Surface form Disambiguated ID Type / Status
Subject Empress Kōjun E19540 entity
Predicate placeOfBirth P1 FINISHED
Object Tokyo, Japan E5560 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: Tokyo, Japan | Statement: [Empress Kōjun, placeOfBirth, Tokyo, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo, Japan
Context triple: [Empress Kōjun, placeOfBirth, Tokyo, Japan]
  • A. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • B. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • C. Toshima, Tokyo
    Toshima, Tokyo is a special ward in northwestern Tokyo known for its major commercial and entertainment hub Ikebukuro and its mix of residential, educational, and cultural institutions.
  • D. Chiyoda, Tokyo, Japan
    Chiyoda is a central special ward of Tokyo that serves as Japan’s political and administrative heart, housing the Imperial Palace, the National Diet, and many government institutions.
  • E. Minato, Tokyo, Japan
    Minato is a central special ward of Tokyo known for its major business districts, foreign embassies, and landmarks such as Tokyo Tower and Roppongi.
  • 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_69a4939e889c8190ac148b3ac1a7f90b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b2caf4088190ab05b22531ecec43 completed March 1, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad795f4874819087c47f1fd989ccff completed March 8, 2026, 1:27 p.m.
Created at: March 1, 2026, 7:39 p.m.