Triple

T10634212
Position Surface form Disambiguated ID Type / Status
Subject Omiya E250535 entity
Predicate connectedTo P37 FINISHED
Object Takasaki E513533 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: Takasaki | Statement: [Omiya, connectedTo, Takasaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Takasaki
Context triple: [Omiya, connectedTo, Takasaki]
  • A. Takasaki chosen
    Takasaki is a city in Japan’s Gunma Prefecture known for its Daruma doll production and as a regional commercial and transportation hub.
  • B. Akishima
    Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
  • C. Maebashi
    Maebashi is the capital city of Gunma Prefecture in Japan, known as a regional administrative and commercial center on the Kantō Plain.
  • D. Nagahama
    Nagahama is a historic lakeside city in central Japan known for its preserved Edo-period streets, Nagahama Castle, and scenic location on the northeastern shore of Lake Biwa.
  • E. Yokkaichi
    Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
  • 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfab47bc819086684edc1b6dce74 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd466577508190b1926c475b7c49dc completed May 8, 2026, 2:11 a.m.
Created at: April 8, 2026, 9:03 p.m.