Triple

T356123
Position Surface form Disambiguated ID Type / Status
Subject North Korea E7545 entity
Predicate writingSystem 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 Korea, writingSystem, Hangul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hangul
Context triple: [North Korea, writingSystem, 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. 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.
  • 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. Kanji
    Kanji are logographic characters of Chinese origin used in the Japanese writing system alongside hiragana and katakana.
  • E. National Institute of Korean Language
    The National Institute of Korean Language is South Korea’s official government body responsible for researching, standardizing, and promoting the Korean language.
  • 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_69a2e7e696948190bebc966535995e45 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebad8bf08190b4a38ffd9157d641 completed Feb. 28, 2026, 1:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e57647d481908d42b10ddebf3ff7 completed March 1, 2026, 7:06 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.