Triple

T14069442
Position Surface form Disambiguated ID Type / Status
Subject National Route 136 E338563 entity
Predicate passesThrough P225 FINISHED
Object Nishiizu NE NERFINISHED

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: Nishiizu | Statement: [National Route 136, passesThrough, Nishiizu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nishiizu
Context triple: [National Route 136, passesThrough, Nishiizu]
  • A. Nishiizu chosen
    Nishiizu is a coastal town in Shizuoka Prefecture, Japan, known for its rugged seaside scenery, hot springs, and views of Suruga Bay.
  • B. Shinshiro
    Shinshiro is a city in eastern Aichi Prefecture, Japan, known for its mountainous scenery, historic battle sites, and traditional rural landscapes.
  • C. Shimotsuki
    Shimotsuki was a Japanese destroyer of the Imperial Japanese Navy that served in World War II before being sunk in late 1944.
  • D. Ikizu
    The Ikizu are an ethnic group native to northwestern Tanzania, traditionally inhabiting areas within the Kagera Region.
  • E. Izutsu
    Izutsu is a classical Noh play, traditionally attributed to Zeami Motokiyo, that poignantly depicts love, memory, and longing through the story of a woman haunted by her past.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de568d0404819087e0fe37c72162cb completed April 14, 2026, 3 p.m.
Created at: April 9, 2026, 10:21 p.m.