Triple

T5036524
Position Surface form Disambiguated ID Type / Status
Subject Koreans E113436 entity
Predicate historicalWritingSystem P1558 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: [Koreans, historicalWritingSystem, Hanja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hanja
Context triple: [Koreans, historicalWritingSystem, 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. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • D. Hangul Jamo Extended-A
    Hangul Jamo Extended-A is a Unicode block that contains additional archaic and extended Hangul jamo characters used for representing Old Korean and specialized orthographic forms.
  • E. Hangul Jamo Extended-B
    Hangul Jamo Extended-B is a Unicode block that contains additional archaic and rare Hangul jamo characters used for scholarly and historical representation of Korean script.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73bb069c8190af86f1b2f95f3d95 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea479f01c8190a84ff4973845eb17 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:37 p.m.