Triple

T6513169
Position Surface form Disambiguated ID Type / Status
Subject Sojin E148185 entity
Predicate writingSystem P454 FINISHED
Object Kanji E2128 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: Kanji | Statement: [Sojin, writingSystem, Kanji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanji
Context triple: [Sojin, writingSystem, Kanji]
  • A. Kanji chosen
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • B. Kana
    Kana is the Japanese syllabic writing system comprising hiragana and katakana, used to represent native words, grammatical elements, and foreign terms.
  • C. Hiragana
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • D. Katakana
    Katakana is one of the two main Japanese phonetic writing systems, primarily used for foreign words, onomatopoeia, emphasis, and technical or scientific terms.
  • E. Chinese characters
    Chinese characters are logographic symbols used for writing the Chinese language and several other East Asian languages, each typically representing a morpheme or meaningful unit.
  • 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_69c687e68e748190baceb9298f32d3ed completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69f3db330819092503af4fb0649ea completed March 27, 2026, 3:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb69ca0c8190954dbe6c627981f3 completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:44 p.m.