Triple

T11934274
Position Surface form Disambiguated ID Type / Status
Subject 文京区 E283998 entity
Predicate containsDistrict P22582 FINISHED
Object 根津
根津は東京都文京区に位置し、古い町並みと根津神社で知られる歴史ある下町エリアです。
 E954801 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: 根津 | Statement: [文京区, containsDistrict, 根津]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 根津
Context triple: [文京区, containsDistrict, 根津]
  • A. Nantan
    Nantan is a city in central Kyoto Prefecture, Japan, known for its rural landscapes, forests, and traditional cultural sites.
  • B. Shakujii
    Shakujii is a residential district in Nerima, Tokyo, known for its large parks, ponds, and suburban atmosphere.
  • C. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • D. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • E. Semboku
    Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
  • 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: 根津
Triple: [文京区, containsDistrict, 根津]
Generated description
根津は東京都文京区に位置し、古い町並みと根津神社で知られる歴史ある下町エリアです。
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 根津
Target entity description: 根津は東京都文京区に位置し、古い町並みと根津神社で知られる歴史ある下町エリアです。
  • A. Nantan
    Nantan is a city in central Kyoto Prefecture, Japan, known for its rural landscapes, forests, and traditional cultural sites.
  • B. Shakujii
    Shakujii is a residential district in Nerima, Tokyo, known for its large parks, ponds, and suburban atmosphere.
  • C. Marunouchi
    Marunouchi is a central Tokyo business district known for its concentration of corporate headquarters, upscale offices, and proximity to Tokyo Station and the Imperial Palace.
  • D. Tanabe
    Tanabe is a coastal city in Japan known as a gateway to the Kumano Kodo pilgrimage routes and for its scenic natural landscapes.
  • E. Semboku
    Semboku is a city in Akita Prefecture, Japan, known for its historic samurai district in Kakunodate and scenic Lake Tazawa.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90306fcf48190a963d2d1932288d1 completed April 10, 2026, 2:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4407cc2388190b0f849fbeed89ab7 completed May 1, 2026, 5:56 a.m.
NEDg Description generation batch_69f448fc874081908fe05f9d8aff11a3 completed May 1, 2026, 6:32 a.m.
NED2 Entity disambiguation (via description) batch_69f44afdc7b08190bdf47cfcb94c34c8 completed May 1, 2026, 6:41 a.m.
Created at: April 8, 2026, 9:45 p.m.