Triple

T8242555
Position Surface form Disambiguated ID Type / Status
Subject Narita E192571 entity
Predicate hasJapaneseName P9882 FINISHED
Object 成田市
成田市 is a city in Chiba Prefecture, Japan, best known internationally as the location of Narita International Airport, one of the Tokyo area's main gateways.
E721658 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: 成田市 | Statement: [Narita, hasJapaneseName, 成田市]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 成田市
Context triple: [Narita, hasJapaneseName, 成田市]
  • A. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • B. 柏原市
    柏原市は、大阪府南東部に位置し、歴史ある寺社やぶどう栽培などで知られる中規模の都市です。
  • C. 高槻市
    高槻市は、大阪府北部に位置し、京都と大阪の中間にあるベッドタウン兼商工業都市です。
  • D. Ibaraki City
    Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • E. Hadano City
    Hadano City is a municipality in Kanagawa Prefecture, Japan, known for its natural scenery, including views of Mount Ōyama and surrounding mountainous landscapes.
  • 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: 成田市
Triple: [Narita, hasJapaneseName, 成田市]
Generated description
成田市 is a city in Chiba Prefecture, Japan, best known internationally as the location of Narita International Airport, one of the Tokyo area's main gateways.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 成田市
Target entity description: 成田市 is a city in Chiba Prefecture, Japan, best known internationally as the location of Narita International Airport, one of the Tokyo area's main gateways.
  • A. 川越市
    川越市 is a historic city in Saitama Prefecture, Japan, famed for its well-preserved Edo-period streetscapes and traditional warehouse-style buildings that have earned it the nickname "Little Edo."
  • B. 柏原市
    柏原市は、大阪府南東部に位置し、歴史ある寺社やぶどう栽培などで知られる中規模の都市です。
  • C. 高槻市
    高槻市は、大阪府北部に位置し、京都と大阪の中間にあるベッドタウン兼商工業都市です。
  • D. Ibaraki City
    Ibaraki City is a suburban city in northern Osaka Prefecture, Japan, known as a residential and commercial hub between Osaka and Kyoto.
  • E. Hadano City
    Hadano City is a municipality in Kanagawa Prefecture, Japan, known for its natural scenery, including views of Mount Ōyama and surrounding mountainous landscapes.
  • 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_69ca82dc8f148190a2c75a98501a7b91 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb783f67708190a4e1c4078c3a6fb0 completed March 31, 2026, 7:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd351871ac81909f8e4a72a6b99ac3 completed April 1, 2026, 3:09 p.m.
NEDg Description generation batch_69cd37a5d3bc8190801b1b0f09eee462 completed April 1, 2026, 3:20 p.m.
NED2 Entity disambiguation (via description) batch_69cd4edfda788190a29f5d9a7a61f6ed completed April 1, 2026, 4:59 p.m.
Created at: March 30, 2026, 5:47 p.m.