Triple

T19117262
Position Surface form Disambiguated ID Type / Status
Subject Line 6 E467936 entity
Predicate hasLanguageName P15 FINISHED
Object Korean NE NERFINISHED

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 | Statement: [Line 6, hasLanguageName, Korean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korean
Context triple: [Line 6, hasLanguageName, Korean]
  • A. Korean chosen
    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.
  • B. South Korean
    South Korean refers to a citizen or native of the Republic of Korea, a country in East Asia known for its advanced technology, pop culture, and rapid economic development.
  • C. Middle Korean
    Middle Korean is the historical form of the Korean language used roughly from the 10th to the 16th century, known from early written records and crucial for understanding the development of modern Korean.
  • D. Korean Chinese
    Korean Chinese are ethnic Koreans who have historically migrated to and settled in China, forming a distinct minority community with blended Korean and Chinese cultural influences.
  • E. Hangul
    Hangul is the native alphabetic writing system of the Korean language, renowned for its scientific design and ease of learning.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e399a6d8819090a9501ff1637b9d completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.