Triple

T1173236
Position Surface form Disambiguated ID Type / Status
Subject Japonic languages E24960 entity
Predicate writingSystem P454 FINISHED
Object Kana 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: Kana | Statement: [Japonic languages, writingSystem, Kana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kana
Context triple: [Japonic languages, writingSystem, Kana]
  • A. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • B. Hiragana chosen
    Hiragana is a Japanese phonetic syllabary used primarily for native words, grammatical elements, and beginners’ reading and writing.
  • C. Kawi script
    Kawi script is an ancient Brahmic-derived writing system historically used across Java and other parts of Southeast Asia to write Old Javanese and related languages.
  • D. Noto
    Noto is a historic town in southeastern Sicily renowned for its exquisite late Baroque architecture and status as a UNESCO World Heritage Site.
  • E. Shūgiin
    Shūgiin is the lower house of Japan’s National Diet, responsible for passing legislation, approving the budget, and selecting the prime minister.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bcecab688190b21a926874cd98d1 completed March 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac668a135881909b885e2816ee8240 completed March 7, 2026, 5:55 p.m.
Created at: March 1, 2026, 7:45 p.m.