Triple

T7735795
Position Surface form Disambiguated ID Type / Status
Subject Kana E175376 entity
Predicate hasPart P35 FINISHED
Object Hiragana E3828 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: Hiragana | Statement: [Kana, hasPart, Hiragana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hiragana
Context triple: [Kana, hasPart, Hiragana]
  • A. Hiragana chosen
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • B. Katakana
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • C. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • D. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • E. Kunrei-shiki romanization
    Kunrei-shiki romanization is a Japanese romanization system officially standardized in Japan that represents the language’s phonological structure more systematically than the widely used Hepburn system.
  • 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_69c6995f9c60819092e386192bd63c6f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7033afbb881909b7ed2cc8f6c27c3 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be355e04819088598b5c7d61b848 completed March 29, 2026, 5:52 a.m.
Created at: March 27, 2026, 4:06 p.m.