Triple

T7871023
Position Surface form Disambiguated ID Type / Status
Subject Hikifune E182736 entity
Predicate partOf P40 FINISHED
Object Sumida City E332279 NE FINISHED

How this triple was built (2 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: Sumida City | Statement: [Hikifune, partOf, Sumida City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sumida City
Context triple: [Hikifune, partOf, Sumida City]
  • A. Sumida City chosen
    Sumida City is a special ward of Tokyo, Japan, known for landmarks such as the Tokyo Skytree and its traditional downtown neighborhoods.
  • B. Bunkyō City
    Bunkyō City is a special ward in central Tokyo, Japan, known for its universities, historic temples, and quiet residential neighborhoods.
  • C. Shibuya City
    Shibuya City is a major commercial and entertainment district in central Tokyo, Japan, famous for its bustling scramble crossing, youth culture, and fashion scene.
  • D. Bunkyō
    Bunkyō is a central Tokyo ward known for its universities, historic temples, and quiet residential neighborhoods.
  • E. Hachiōji
    Hachiōji is a city in western Tokyo, Japan, known as a regional commercial and educational hub with rich historical sites and access to nearby mountains and nature.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69cd9423b4608190acbe4a3141890a05 completed April 1, 2026, 9:54 p.m.
Created at: March 30, 2026, 4:55 p.m.