Triple

T8354675
Position Surface form Disambiguated ID Type / Status
Subject 中部地方 E196653 entity
Predicate hasShinkansenStation P39390 FINISHED
Object 金沢駅 E573152 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: 金沢駅 | Statement: [中部地方, hasShinkansenStation, 金沢駅]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 金沢駅
Context triple: [中部地方, hasShinkansenStation, 金沢駅]
  • A. Kanazawa Station chosen
    Kanazawa Station is a major railway hub in Ishikawa Prefecture, Japan, known for its striking modern architecture and role as a gateway to the Hokuriku region.
  • B. Nagano Station
    Nagano Station is a major railway hub in Nagano, Japan, serving as a gateway to the region’s ski resorts, temples, and surrounding mountain areas.
  • C. Zushi Station
    Zushi Station is a railway station in Zushi, Kanagawa Prefecture, Japan, served by JR East lines including the Yokosuka Line and Shōnan–Shinjuku Line.
  • D. Kyoto Station
    Kyoto Station is a major railway and transportation hub in Kyoto, Japan, known for its vast, modern architectural complex that integrates trains, buses, shopping, and cultural facilities.
  • E. Nagoya Station
    Nagoya Station is one of Japan’s largest and busiest railway hubs, serving as a major Shinkansen and regional transit center in the city of Nagoya.
  • 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_69ca82f08b348190bfb7881944bbff6f completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cbd120a1ec8190a8dc101fa1371780 completed March 31, 2026, 1:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6ccf66d48190a457e0ea869b278e completed April 2, 2026, 1:19 p.m.
Created at: March 30, 2026, 5:59 p.m.