Triple

T13376175
Position Surface form Disambiguated ID Type / Status
Subject Noda Kōichi E319190 entity
Predicate workLocation P7 FINISHED
Object Kobe E3089 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: Kobe | Statement: [Noda Kōichi, workLocation, Kobe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kobe
Context triple: [Noda Kōichi, workLocation, Kobe]
  • A. Kobe chosen
    Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
  • B. Neo Kobe City
    Neo Kobe City is a futuristic, cyberpunk metropolis shrouded in perpetual rain and noir atmosphere, serving as the primary backdrop for Hideo Kojima’s adventure game Snatcher.
  • C. Kobe Nankinmachi
    Kobe Nankinmachi is a famous Chinatown district in Kobe, Japan, known for its Chinese restaurants, shops, and vibrant cultural festivals.
  • D. Kobe – Naha
    Kobe – Naha is a domestic air route in Japan connecting Kobe in Hyōgo Prefecture with Naha in Okinawa Prefecture.
  • E. Kobe, Hyogo, Japan
    Kobe, Hyogo, Japan is a major port city in western Japan known for its international trade, scenic harbor setting between mountains and sea, and famous Kobe beef.
  • 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_69d806b886bc8190b676e7768b8e01c5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadce3fec48190a5443d87c85477a3 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7397f098c8190a2062d8c1a74d28f completed May 3, 2026, 12:03 p.m.
Created at: April 9, 2026, 9:33 p.m.