Triple

T12018157
Position Surface form Disambiguated ID Type / Status
Subject The Cube shopping mall E286078 entity
Predicate connectedTo P37 FINISHED
Object Kyoto Station 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: Kyoto Station | Statement: [The Cube shopping mall, connectedTo, Kyoto Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyoto Station
Context triple: [The Cube shopping mall, connectedTo, Kyoto Station]
  • A. Kyoto Station chosen
    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.
  • B. Osaka Station
    Osaka Station is a major railway terminal and transportation hub in Osaka, Japan, serving numerous local and long-distance train lines and connecting key commercial districts.
  • C. 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.
  • D. Suita Station
    Suita Station is a railway station in Suita, Osaka Prefecture, Japan, serving passengers on the JR Kyoto Line (Tōkaidō Main Line).
  • E. Tokyo Station
    Tokyo Station is a major railway hub in central Tokyo, serving as a key terminal for Shinkansen bullet trains and numerous local and regional lines.
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903dabf2c819084dcaa05ae0a6018 completed April 10, 2026, 2:06 p.m.
Created at: April 8, 2026, 9:47 p.m.