Triple

T224253
Position Surface form Disambiguated ID Type / Status
Subject Busan E4279 entity
Predicate sisterCity P1072 FINISHED
Object Fukuoka E38549 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: Fukuoka | Statement: [Busan, sisterCity, Fukuoka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fukuoka
Context triple: [Busan, sisterCity, Fukuoka]
  • A. Fukuoka chosen
    Fukuoka is a major Japanese city on the northern shore of Kyushu, known as an important economic, cultural, and transportation hub with a busy international port.
  • B. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • 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. 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. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • 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_69a2573508588190b522c2476d91acfe completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c7194fc8190a2d02d446ae3a75e completed Feb. 28, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69a4a146fcc8819095b8d793864fbab1 completed March 1, 2026, 8:27 p.m.
Created at: Feb. 28, 2026, 2:53 a.m.