Triple

T262042
Position Surface form Disambiguated ID Type / Status
Subject Tokyo E5560 entity
Predicate contains P35 FINISHED
Object Haneda Airport
Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
E35463 NE FINISHED

How this triple was built (4 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: Haneda Airport | Statement: [Tokyo, contains, Haneda Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haneda Airport
Context triple: [Tokyo, contains, Haneda Airport]
  • A. Kansai International Airport
    Kansai International Airport is a major international airport in Japan built on an artificial island in Osaka Bay, serving as a key gateway to the Kansai region.
  • B. Kobe Airport
    Kobe Airport is a regional airport located on an artificial island off the coast of Kobe, Japan, primarily serving domestic flights.
  • C. Osaka International Airport
    Osaka International Airport is a major Japanese airport serving the Osaka metropolitan area, primarily handling domestic flights and known locally as Itami Airport.
  • D. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • E. Port of Kobe
    The Port of Kobe is one of Japan’s major international seaports, serving as a key hub for container shipping and maritime trade in the Kansai region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Haneda Airport
Triple: [Tokyo, contains, Haneda Airport]
Generated description
Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haneda Airport
Target entity description: Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
  • A. Kansai International Airport
    Kansai International Airport is a major international airport in Japan built on an artificial island in Osaka Bay, serving as a key gateway to the Kansai region.
  • B. Kobe Airport
    Kobe Airport is a regional airport located on an artificial island off the coast of Kobe, Japan, primarily serving domestic flights.
  • C. Osaka International Airport
    Osaka International Airport is a major Japanese airport serving the Osaka metropolitan area, primarily handling domestic flights and known locally as Itami Airport.
  • D. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • E. Port of Kobe
    The Port of Kobe is one of Japan’s major international seaports, serving as a key hub for container shipping and maritime trade in the Kansai region.
  • F. None of above. chosen

Provenance (5 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d7428dc8190ae12b12a21fcc6cb completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69a38f4e35688190b8c8714c7f06c6ee completed March 1, 2026, 12:58 a.m.
NEDg Description generation batch_69a390159ac08190892a67e906b33df3 completed March 1, 2026, 1:02 a.m.
NED2 Entity disambiguation (via description) batch_69a3907070fc8190891fac451c8f7fad completed March 1, 2026, 1:03 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.