Triple

T14167058
Position Surface form Disambiguated ID Type / Status
Subject 千代田区 E351107 entity
Predicate contains P35 FINISHED
Object 神保町
神保町 is a Tokyo neighborhood famed as Japan’s largest used-book district, lined with countless bookstores, publishers, and cozy cafés.
E1086395 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: 神保町 | Statement: [千代田区, contains, 神保町]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 神保町
Context triple: [千代田区, contains, 神保町]
  • A. 大手町
    大手町 is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • B. 神宮前
    神宮前 is a district in Shibuya, Tokyo, known for its proximity to Meiji Shrine and the fashionable Harajuku and Omotesando areas.
  • C. 高田馬場
    高田馬場 is a bustling neighborhood in Tokyo’s Shinjuku ward known for its major train station, student population, and numerous eateries and entertainment spots.
  • D. 半蔵門
    半蔵門は、東京都千代田区に位置する皇居の西側に設けられた門で、江戸城時代からの歴史を持つ重要な出入口です。
  • E. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • 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: 神保町
Triple: [千代田区, contains, 神保町]
Generated description
神保町 is a Tokyo neighborhood famed as Japan’s largest used-book district, lined with countless bookstores, publishers, and cozy cafés.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 神保町
Target entity description: 神保町 is a Tokyo neighborhood famed as Japan’s largest used-book district, lined with countless bookstores, publishers, and cozy cafés.
  • A. 大手町
    大手町 is a major business district in central Tokyo known for its concentration of corporate headquarters, financial institutions, and proximity to the Imperial Palace.
  • B. 神宮前
    神宮前 is a district in Shibuya, Tokyo, known for its proximity to Meiji Shrine and the fashionable Harajuku and Omotesando areas.
  • C. 高田馬場
    高田馬場 is a bustling neighborhood in Tokyo’s Shinjuku ward known for its major train station, student population, and numerous eateries and entertainment spots.
  • D. 半蔵門
    半蔵門は、東京都千代田区に位置する皇居の西側に設けられた門で、江戸城時代からの歴史を持つ重要な出入口です。
  • E. Nagatacho
    Nagatacho is a central district in Tokyo, Japan, known as the political heart of the country and home to key government institutions such as the National Diet Building.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b355f08190864c7322bbcb766d completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd193dbbcc819082043d92c174164c completed May 7, 2026, 10:59 p.m.
NEDg Description generation batch_69fd1d57dfa88190a4cd9b6fceddbc3b completed May 7, 2026, 11:16 p.m.
NED2 Entity disambiguation (via description) batch_69fd1e267dcc819087a24cbfea2736db completed May 7, 2026, 11:20 p.m.
Created at: April 10, 2026, 1 a.m.