Triple

T7870891
Position Surface form Disambiguated ID Type / Status
Subject Katsushika E182733 entity
Predicate containsDistrict P22582 FINISHED
Object Shin-Koiwa
Shin-Koiwa is a residential and commercial neighborhood in Tokyo known for its busy railway station, local shopping streets, and traditional shitamachi atmosphere.
 E708185 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: Shin-Koiwa | Statement: [Katsushika, containsDistrict, Shin-Koiwa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shin-Koiwa
Context triple: [Katsushika, containsDistrict, Shin-Koiwa]
  • A. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • B. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • C. Takamori
    Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
  • D. Kinsaku
    Kinsaku is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and literary figure.
  • E. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • 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: Shin-Koiwa
Triple: [Katsushika, containsDistrict, Shin-Koiwa]
Generated description
Shin-Koiwa is a residential and commercial neighborhood in Tokyo known for its busy railway station, local shopping streets, and traditional shitamachi atmosphere.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shin-Koiwa
Target entity description: Shin-Koiwa is a residential and commercial neighborhood in Tokyo known for its busy railway station, local shopping streets, and traditional shitamachi atmosphere.
  • A. Takanami
    Takanami was a Japanese destroyer of the Imperial Japanese Navy during World War II, notable for being sunk in the Battle of Tassafaronga in 1942.
  • B. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • C. Takamori
    Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
  • D. Kinsaku
    Kinsaku is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and literary figure.
  • E. Kentarō
    Kentarō is a Japanese given name commonly used for males, often associated with traditional or strong-sounding name combinations.
  • 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_69ca82894d9081908a832bfce71a4714 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb384a285881908a5b2de278f9556f completed March 31, 2026, 2:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc5615a38c8190b11af9fe5b2e1422 completed March 31, 2026, 11:17 p.m.
NEDg Description generation batch_69cc58a76b90819092de63b3b23e70af completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cfccc9c8190adcbaee96c17711e completed March 31, 2026, 11:47 p.m.
Created at: March 30, 2026, 4:55 p.m.