Triple

T13036086
Position Surface form Disambiguated ID Type / Status
Subject 42 (school) E326563 entity
Predicate hasCampus P116 FINISHED
Object 42 Seoul
42 Seoul is the South Korean campus of the global, tuition-free 42 coding school network, offering peer-to-peer, project-based programming education.
E19209 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: 42 Seoul | Statement: [42 (school), hasCampus, 42 Seoul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 42 Seoul
Context triple: [42 (school), hasCampus, 42 Seoul]
  • A. Daegu, South Korea
    Daegu, South Korea is a major city in the southeastern part of the country known for its role as an industrial, cultural, and educational center.
  • B. Seoul
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • C. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • D. Busan, South Korea
    Busan, South Korea is the country’s second-largest city and a major coastal hub known for its busy port, beaches, and international film festival.
  • E. Gwangju
    Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
  • 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: 42 Seoul
Triple: [42 (school), hasCampus, 42 Seoul]
Generated description
42 Seoul is the South Korean campus of the global, tuition-free 42 coding school network, offering peer-to-peer, project-based programming education.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 42 Seoul
Target entity description: 42 Seoul is the South Korean campus of the global, tuition-free 42 coding school network, offering peer-to-peer, project-based programming education.
  • A. Daegu, South Korea
    Daegu, South Korea is a major city in the southeastern part of the country known for its role as an industrial, cultural, and educational center.
  • B. Seoul chosen
    Seoul is the capital and largest metropolis of South Korea, known as a major global center for technology, culture, and finance.
  • C. Daegu
    Daegu is a major metropolitan city in southeastern South Korea known for its textile industry, electronics manufacturing, and cultural festivals.
  • D. Busan, South Korea
    Busan, South Korea is the country’s second-largest city and a major coastal hub known for its busy port, beaches, and international film festival.
  • E. Gwangju
    Gwangju is a major metropolitan city in southwestern South Korea known for its rich cultural heritage and pivotal role in the country’s pro-democracy movement.
  • F. None of above.

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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97f2a71a0819098bb6cf8a4b2208a completed April 10, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c1ee7048190b2571364b25bd49d completed May 8, 2026, 2:36 a.m.
NEDg Description generation batch_69fd4cc76178819086fb9a9b6b5cfd05 completed May 8, 2026, 2:39 a.m.
NED2 Entity disambiguation (via description) batch_69fd4dcc41c481908f0d7e05c4c176ee completed May 8, 2026, 2:43 a.m.
Created at: April 9, 2026, 8:55 p.m.