Triple

T6402739
Position Surface form Disambiguated ID Type / Status
Subject Takasaki Line E144100 entity
Predicate namedAfter P63 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: [Takasaki Line, namedAfter, Takasaki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Takasaki
Context triple: [Takasaki Line, namedAfter, 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068af3f448190a94ecd5109e9e8e4 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d380b6a39c8190ade06ba0249ffa79 completed April 6, 2026, 9:45 a.m.
Created at: March 22, 2026, 4:35 p.m.