Triple

T675136
Position Surface form Disambiguated ID Type / Status
Subject Heisei E13061 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: [Heisei, writingSystem, Kanji]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanji
Context triple: [Heisei, writingSystem, Kanji]
  • A. Kanji chosen
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • B. Hiragana
    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. Hangul
    Hangul is the native alphabetic writing system of the Korean language, renowned for its scientific design and ease of learning.
  • E. Yapese
    Yapese is an Austronesian language spoken primarily on the island of Yap and nearby islands in the western Pacific.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a0266e7c8190a94c4b4b761c59f4 completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5c3a1b6588190b0c9215afb3a9200 completed March 2, 2026, 5:06 p.m.
Created at: March 1, 2026, 7:36 p.m.