Triple

T4216316
Position Surface form Disambiguated ID Type / Status
Subject Kencho-mae Station E94224 entity
Predicate near P350 FINISHED
Object Naha City Hall
Naha City Hall is the main municipal government building and administrative center of Naha, the capital city of Okinawa Prefecture in Japan.
 E425138 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: Naha City Hall | Statement: [Kencho-mae Station, near, Naha City Hall]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Naha City Hall
Context triple: [Kencho-mae Station, near, Naha City Hall]
  • A. Hadano City Hall
    Hadano City Hall is the main municipal government building and administrative center serving the city of Hadano in Kanagawa Prefecture, Japan.
  • B. Uruma City Hall
    Uruma City Hall is the main municipal government building and administrative center serving the city of Uruma in Okinawa Prefecture, Japan.
  • C. Nagoya City Hall
    Nagoya City Hall is the central municipal government building and administrative headquarters of the city of Nagoya, Japan.
  • D. Minato City Hall
    Minato City Hall is the main administrative government building serving Tokyo’s Minato ward.
  • E. Mishima City Hall
    Mishima City Hall is the main municipal government building and administrative center serving the city of Mishima in Shizuoka Prefecture, Japan.
  • 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: Naha City Hall
Triple: [Kencho-mae Station, near, Naha City Hall]
Generated description
Naha City Hall is the main municipal government building and administrative center of Naha, the capital city of Okinawa Prefecture in Japan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Naha City Hall
Target entity description: Naha City Hall is the main municipal government building and administrative center of Naha, the capital city of Okinawa Prefecture in Japan.
  • A. Hadano City Hall
    Hadano City Hall is the main municipal government building and administrative center serving the city of Hadano in Kanagawa Prefecture, Japan.
  • B. Uruma City Hall
    Uruma City Hall is the main municipal government building and administrative center serving the city of Uruma in Okinawa Prefecture, Japan.
  • C. Nagoya City Hall
    Nagoya City Hall is the central municipal government building and administrative headquarters of the city of Nagoya, Japan.
  • D. Minato City Hall
    Minato City Hall is the main administrative government building serving Tokyo’s Minato ward.
  • E. Mishima City Hall
    Mishima City Hall is the main municipal government building and administrative center serving the city of Mishima in Shizuoka Prefecture, Japan.
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34bea284081909beaded9873f0852 completed March 12, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a852e0448190bc488087e92a94d4 completed March 14, 2026, 6:26 p.m.
NEDg Description generation batch_69b5a8e024a081909e7ecbe969793281 completed March 14, 2026, 6:28 p.m.
NED2 Entity disambiguation (via description) batch_69b5acefd1f881908226ff68a741552b completed March 14, 2026, 6:46 p.m.
Created at: March 12, 2026, 11:04 p.m.