Triple

T5778195
Position Surface form Disambiguated ID Type / Status
Subject Joseongeul E127495 entity
Predicate writingSystemFamily P9330 FINISHED
Object Korean scripts 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: Korean scripts | Statement: [Joseongeul, writingSystemFamily, Korean scripts]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korean scripts
Context triple: [Joseongeul, writingSystemFamily, Korean scripts]
  • 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. Sorabe script
    The Sorabe script is an Arabic-derived writing system historically used by Malagasy speakers, particularly in southern Madagascar, for religious, literary, and administrative texts.
  • D. Jurchen script
    The Jurchen script was a writing system developed by the Jurchen people to record their Tungusic language, used primarily during the Jin dynasty in northern China.
  • E. 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.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e107348190a03086f1cbfae0d3 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e6fd260819090d5e3c877c8bd31 completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:50 p.m.