Triple

T14437321
Position Surface form Disambiguated ID Type / Status
Subject Denpoin-dori E357998 entity
Predicate locatedIn P40 FINISHED
Object Taito-ku
Taito-ku is a special ward in central Tokyo, Japan, known for historic districts like Asakusa and Ueno, major temples, museums, and traditional shopping streets.
 E1099291 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: Taito-ku | Statement: [Denpoin-dori, locatedIn, Taito-ku]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taito-ku
Context triple: [Denpoin-dori, locatedIn, Taito-ku]
  • A. Daitō
    Daitō is a city in Osaka Prefecture, Japan, known as a residential and light industrial suburb within the Osaka metropolitan area.
  • B. Taketa
    Taketa is a small historic city in Japan known for its scenic rural landscapes, hot springs, and castle ruins.
  • C. Tsutsumi
    Tsutsumi is a Japanese surname associated with several notable figures in business, politics, and the arts in Japan.
  • D. Kōta
    Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
  • E. Kujūkuri
    Kujūkuri is a long, sandy coastal town and beach area on the eastern shore of Chiba Prefecture, Japan, known for its surfing spots and scenic Pacific shoreline.
  • 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: Taito-ku
Triple: [Denpoin-dori, locatedIn, Taito-ku]
Generated description
Taito-ku is a special ward in central Tokyo, Japan, known for historic districts like Asakusa and Ueno, major temples, museums, and traditional shopping streets.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taito-ku
Target entity description: Taito-ku is a special ward in central Tokyo, Japan, known for historic districts like Asakusa and Ueno, major temples, museums, and traditional shopping streets.
  • A. Daitō
    Daitō is a city in Osaka Prefecture, Japan, known as a residential and light industrial suburb within the Osaka metropolitan area.
  • B. Taketa
    Taketa is a small historic city in Japan known for its scenic rural landscapes, hot springs, and castle ruins.
  • C. Tsutsumi
    Tsutsumi is a Japanese surname associated with several notable figures in business, politics, and the arts in Japan.
  • D. Kōta
    Kōta is a town in central Japan known for its manufacturing industries and location within Aichi Prefecture.
  • E. Kujūkuri
    Kujūkuri is a long, sandy coastal town and beach area on the eastern shore of Chiba Prefecture, Japan, known for its surfing spots and scenic Pacific shoreline.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914a45ec81909ab8ccf302047d7f completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd7f46881908df1a1cea7b6af9b completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5d585cc08190908bc5f9b8abdb82 completed May 8, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69fd5e0bbd6c8190b14039b3335692c7 completed May 8, 2026, 3:52 a.m.
Created at: April 10, 2026, 1:18 a.m.