Triple

T4590466
Position Surface form Disambiguated ID Type / Status
Subject Nishi-ku, Yokohama E103473 entity
Predicate locatedIn P40 FINISHED
Object Yokohama E10676 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: Yokohama | Statement: [Nishi-ku, Yokohama, locatedIn, Yokohama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yokohama
Context triple: [Nishi-ku, Yokohama, locatedIn, Yokohama]
  • A. Yokohama chosen
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • B. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • C. Tokyo
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • D. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • E. Osaka
    Osaka is Japan's third-largest city and a major economic, cultural, and historical hub known for its vibrant street food, bustling nightlife, and role as a commercial center in the Kansai region.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5923c0c88190952137d448d474cf completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf185542508190ad71b753bda5d1a3 completed March 21, 2026, 10:14 p.m.
Created at: March 20, 2026, 1:11 p.m.