Triple

T21519901
Position Surface form Disambiguated ID Type / Status
Subject Mukō E530944 entity
Predicate adjacentTo P224 FINISHED
Object Nagaokakyō 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: Nagaokakyō | Statement: [Mukō, adjacentTo, Nagaokakyō]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagaokakyō
Context triple: [Mukō, adjacentTo, Nagaokakyō]
  • A. Nagaokakyo chosen
    Nagaokakyo is a suburban city in Japan known for its bamboo groves, historical temples, and convenient location between Kyoto and Osaka.
  • B. Futakotamagawa
    Futakotamagawa is a riverside commercial and residential district in Tokyo known for its large shopping complexes, upscale housing, and scenic Tama River views.
  • C. Kizugawa
    Kizugawa is a city in southern Kyoto Prefecture, Japan, known for its mix of historical sites, residential areas, and growing industrial and research facilities.
  • D. Kizugawa
    Kizugawa is a major district within Naniwa-ku in Osaka, Japan, known as part of the city's central urban area.
  • E. Sakuragawa
    Sakuragawa is a neighborhood in Osaka, Japan, known as one of the major districts within Naniwa Ward.
  • 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_69e0c45d95a081908e7962ad215da746 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee884af0f08190bc1f3d70e57a325d completed April 26, 2026, 9:48 p.m.
Created at: April 16, 2026, 6:26 p.m.