Triple

T13085478
Position Surface form Disambiguated ID Type / Status
Subject Masayoshi Haneda E310319 entity
Predicate hasFamilyName P18 FINISHED
Object Haneda
Haneda is a Japanese surname commonly borne by individuals in Japan.
E1040025 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 | Statement: [Masayoshi Haneda, hasFamilyName, Haneda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haneda
Context triple: [Masayoshi Haneda, hasFamilyName, Haneda]
  • A. Miyazaki–Tokyo Haneda
    Miyazaki–Tokyo Haneda is a domestic air route in Japan connecting Miyazaki Airport on Kyushu with Tokyo’s centrally located Haneda Airport.
  • B. Naha–Tokyo Haneda
    Naha–Tokyo Haneda is a major domestic air route in Japan connecting Okinawa’s capital Naha with Tokyo’s centrally located Haneda Airport.
  • C. Haneda Airport
    Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
  • D. Kobe Airport
    Kobe Airport is a regional airport located on an artificial island off the coast of Kobe, Japan, primarily serving domestic flights.
  • E. Tezu Airport
    Tezu Airport is a regional airport in Arunachal Pradesh, India, serving the town of Tezu and improving air connectivity in the remote northeastern 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
Triple: [Masayoshi Haneda, hasFamilyName, Haneda]
Generated description
Haneda is a Japanese surname commonly borne by individuals in Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Haneda
Target entity description: Haneda is a Japanese surname commonly borne by individuals in Japan.
  • A. Miyazaki–Tokyo Haneda
    Miyazaki–Tokyo Haneda is a domestic air route in Japan connecting Miyazaki Airport on Kyushu with Tokyo’s centrally located Haneda Airport.
  • B. Naha–Tokyo Haneda
    Naha–Tokyo Haneda is a major domestic air route in Japan connecting Okinawa’s capital Naha with Tokyo’s centrally located Haneda Airport.
  • C. Haneda Airport
    Haneda Airport is one of Tokyo’s primary international airports and one of Japan’s busiest air travel hubs.
  • D. Kobe Airport
    Kobe Airport is a regional airport located on an artificial island off the coast of Kobe, Japan, primarily serving domestic flights.
  • E. Tezu Airport
    Tezu Airport is a regional airport in Arunachal Pradesh, India, serving the town of Tezu and improving air connectivity in the remote northeastern 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d981361e8c819099376435aa3a7aa3 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7396e6cf881908b4cc3836501ed08 completed May 3, 2026, 12:02 p.m.
NEDg Description generation batch_69f73a7ca9048190948c1bceede2a09c completed May 3, 2026, 12:07 p.m.
NED2 Entity disambiguation (via description) batch_69f73abc1c9481909d509eb02bafd909 completed May 3, 2026, 12:08 p.m.
Created at: April 9, 2026, 9:02 p.m.