Triple

T5905082
Position Surface form Disambiguated ID Type / Status
Subject 皇居 E131323 entity
Predicate 所在地 P40 FINISHED
Object 東京都 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: 東京都 | Statement: [皇居, 所在地, 東京都]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 東京都
Context triple: [皇居, 所在地, 東京都]
  • A. Tokyo Prefecture
    Tokyo Prefecture is Japan’s capital metropolitan region, encompassing the city of Tokyo and serving as the country’s political, economic, and cultural center.
  • B. Tōkyō-wan
    Tōkyō-wan is the Japanese name for Tokyo Bay, a major urban bay on the Pacific coast of Honshu that serves as a key economic and transportation hub for the Greater Tokyo Area.
  • C. Tokyo chosen
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • D. Chūō, Tokyo
    Chūō, Tokyo is a central ward of Tokyo known as a major commercial and financial district that includes areas like Nihonbashi and Ginza.
  • E. Hachiōji
    Hachiōji is a city in western Tokyo, Japan, known as a regional commercial and educational hub with rich historical sites and access to nearby mountains and nature.
  • 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_69c0085864a88190a569c05ff7d65f29 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c049fdb3e08190a72337ab4f48bc8e completed March 22, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c16e882cdc819082b46b9380c430ad completed March 23, 2026, 4:47 p.m.
Created at: March 22, 2026, 3:59 p.m.