Triple

T5778185
Position Surface form Disambiguated ID Type / Status
Subject Joseongeul E127495 entity
Predicate historicalName P65 FINISHED
Object Gukmun
Gukmun is an old Korean term referring to the native Korean writing system that later came to be known as Joseongeul or Hangul.
 E549418 NE FINISHED

How this triple was built (4 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: Gukmun | Statement: [Joseongeul, historicalName, Gukmun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gukmun
Context triple: [Joseongeul, historicalName, Gukmun]
  • A. Gwan-eum
    Gwan-eum is the Korean name for Guanyin, the bodhisattva of compassion widely revered in East Asian Buddhism.
  • B. Seochon
    Seochon is a historic neighborhood in central Seoul known for its traditional hanok houses, narrow alleyways, and vibrant mix of old Korean culture and modern cafes and galleries.
  • C. Baeggu
    Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
  • D. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • E. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gukmun
Triple: [Joseongeul, historicalName, Gukmun]
Generated description
Gukmun is an old Korean term referring to the native Korean writing system that later came to be known as Joseongeul or Hangul.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gukmun
Target entity description: Gukmun is an old Korean term referring to the native Korean writing system that later came to be known as Joseongeul or Hangul.
  • A. Gwan-eum
    Gwan-eum is the Korean name for Guanyin, the bodhisattva of compassion widely revered in East Asian Buddhism.
  • B. Seochon
    Seochon is a historic neighborhood in central Seoul known for its traditional hanok houses, narrow alleyways, and vibrant mix of old Korean culture and modern cafes and galleries.
  • C. Baeggu
    Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
  • D. Wiryeseong
    Wiryeseong was the first capital city of the ancient Korean kingdom of Baekje, located in the Han River basin near present-day Seoul.
  • E. Munji
    Munji is a lesser-known Eastern Iranian language spoken by the Munji people in the remote Munjan Valley of northeastern Afghanistan.
  • F. None of above. chosen

Provenance (5 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_69c0a17276648190b1fedfcc69d46b59 completed March 23, 2026, 2:12 a.m.
NEDg Description generation batch_69c0a1fc8d888190baf5547a43b87bb6 completed March 23, 2026, 2:14 a.m.
NED2 Entity disambiguation (via description) batch_69c0a260a0e48190a72805ba2c925c20 completed March 23, 2026, 2:16 a.m.
Created at: March 22, 2026, 3:50 p.m.