Triple

T7636176
Position Surface form Disambiguated ID Type / Status
Subject Yue E172883 entity
Predicate isWrittenWithScript P454 FINISHED
Object Hanja E139773 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: Hanja | Statement: [Yue, isWrittenWithScript, Hanja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanja
Context triple: [Yue, isWrittenWithScript, Hanja]
  • A. Hanja chosen
    Hanja is the set of traditional Chinese characters historically used to write Korean, especially for proper names, academic terms, and classical texts.
  • B. Hangul
    Hangul is the native alphabetic writing system of the Korean language, renowned for its scientific design and ease of learning.
  • C. Hangul Jamo
    Hangul Jamo is a Unicode block that encodes the individual consonant and vowel letters used to write the Korean Hangul script.
  • D. Hangul Syllables
    Hangul Syllables is the Unicode block that encodes the precomposed modern Korean syllabic characters used for writing Hangul.
  • 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_69c69952849881908fdcea7a93bfc307 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c701731a288190b53ffc546a2f47d7 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870c33ce081908df916d769fa84be completed March 29, 2026, 12:22 a.m.
Created at: March 27, 2026, 3:57 p.m.