Triple

T17966259
Position Surface form Disambiguated ID Type / Status
Subject Matsue E449214 entity
Predicate hasLandmark P105 FINISHED
Object Nakaumi 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: Nakaumi | Statement: [Matsue, hasLandmark, Nakaumi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nakaumi
Context triple: [Matsue, hasLandmark, Nakaumi]
  • A. Nakaumi chosen
    Nakaumi is a brackish lake in western Japan, situated between Tottori and Shimane Prefectures and known for its rich ecosystems and scenic coastal landscapes.
  • B. Takamori
    Takamori is the given name of Saigō Takamori, a prominent 19th-century Japanese samurai and political figure often called the "last true samurai."
  • C. Takayoshi
    Takayoshi is a Japanese given name notably borne by Kido Takayoshi, a key samurai and statesman of the Meiji Restoration.
  • D. Hiranuma
    Hiranuma is a notable district within Nishi Ward in Yokohama, Japan, known as part of the city’s central urban area.
  • E. Shirō
    Shirō is a Japanese given name most infamously associated with Shirō Ishii, the Imperial Japanese Army general who led the biological warfare research unit known as Unit 731 during World War II.
  • 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b1380960819089a3c0dd7cd57e5e completed April 19, 2026, 10:40 a.m.
Created at: April 10, 2026, 10:22 a.m.