Triple

T11026727
Position Surface form Disambiguated ID Type / Status
Subject Yukio E260643 entity
Predicate writingSystem P454 FINISHED
Object Katakana E154499 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: Katakana | Statement: [Yukio, writingSystem, Katakana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katakana
Context triple: [Yukio, writingSystem, Katakana]
  • A. Katakana chosen
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • B. Hiragana
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • C. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • D. Kana
    Kana is a settlement located within Pakistan’s Shangla District in the Khyber Pakhtunkhwa province.
  • E. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797d190f08190bcb5949ee24306f1 completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a997d7bc8190982467039e0f5504 completed April 18, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:25 p.m.