Triple

T8525720
Position Surface form Disambiguated ID Type / Status
Subject Shintaro E201810 entity
Predicate canHaveMultipleKanjiSpellings P59069 FINISHED
Object true LITERAL 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: true | Statement: [Shintaro, canHaveMultipleKanjiSpellings, true]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: canHaveMultipleKanjiSpellings
Context triple: [Shintaro, canHaveMultipleKanjiSpellings, true]
  • A. canBeWrittenWithMultipleKanji chosen
    Indicates that the same word or expression can be represented using more than one distinct kanji spelling.
  • B. typicalKanjiSpelling
    Indicates that one written form is the standard or most commonly used kanji spelling for another expression (such as a word or phrase).
  • C. hasVariantSpelling
    Indicates that one term is an alternative spelling form of another term.
  • D. usesKanjiFrom
    Indicates that one writing system, word, or text incorporates or is composed of kanji characters originating from another specified source.
  • E. meaningDependsOnKanji
    Indicates that the meaning of something (e.g., a word or expression) is determined by, or varies according to, the specific kanji characters used.
  • F. None of above.

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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe6463fe48190b6d3482212356be1 completed March 31, 2026, 3:20 p.m.
PD Predicate disambiguation batch_69cbd10f64b4819080859057c19e58f0 completed March 31, 2026, 1:50 p.m.
Created at: March 30, 2026, 6:16 p.m.