Triple

T5710685
Position Surface form Disambiguated ID Type / Status
Subject North Korean media E125899 entity
Predicate usesWritingSystem P454 FINISHED
Object Hangul E25453 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: Hangul | Statement: [North Korean media, usesWritingSystem, Hangul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hangul
Context triple: [North Korean media, usesWritingSystem, Hangul]
  • A. Hangul chosen
    Hangul is the native alphabetic writing system of the Korean language, renowned for its scientific design and ease of learning.
  • B. Hanja
    Hanja is the set of traditional Chinese characters historically used to write Korean, especially for proper names, academic terms, and classical texts.
  • C. Korean
    Korean is an East Asian language spoken primarily in both North and South Korea, known for its unique Hangul writing system and distinct linguistic structure.
  • D. Hangul Jamo
    Hangul Jamo is a Unicode block that encodes the individual consonant and vowel letters used to write the Korean Hangul script.
  • E. Hangul Syllables
    Hangul Syllables is the Unicode block that encodes the precomposed modern Korean syllabic characters used for writing Hangul.
  • 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_69c0082d6fe48190b777fb383769e5c8 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0248df1a8819091e9f3c80dba3f54 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0b3412c8190a4b97863e060e928 completed March 23, 2026, 3:17 a.m.
Created at: March 22, 2026, 3:46 p.m.