Triple

T130898
Position Surface form Disambiguated ID Type / Status
Subject Memphis, Tennessee E2650 entity
Predicate sisterCity P1072 FINISHED
Object Yokohama, Japan 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, Japan | Statement: [Memphis, Tennessee, sisterCity, Yokohama, Japan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yokohama, Japan
Context triple: [Memphis, Tennessee, sisterCity, Yokohama, Japan]
  • A. Yokohama chosen
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • B. 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.
  • C. Nagoya
    Nagoya is a major industrial and commercial city in central Japan, known as a manufacturing hub and the capital of Aichi Prefecture.
  • D. Tokyo
    Tokyo is Japan’s largest metropolis and a global center of finance, culture, technology, and transportation.
  • E. Moriguchi
    Moriguchi is a city in Japan’s Kansai region that forms part of the Osaka metropolitan area and serves as a residential and commercial hub.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a25785ad5c819097c00f31719fea7e completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3f09f2838819089a4ee40286281a2 completed March 1, 2026, 7:54 a.m.
Created at: Feb. 28, 2026, 2:30 a.m.