Triple

T12754462
Position Surface form Disambiguated ID Type / Status
Subject College of Liberal Arts, Yonsei University E304820 entity
Predicate offersMajorIn P42231 FINISHED
Object Korean language and literature LITERAL 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 language and literature | Statement: [College of Liberal Arts, Yonsei University, offersMajorIn, Korean language and literature]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: offersMajorIn
Context triple: [College of Liberal Arts, Yonsei University, offersMajorIn, Korean language and literature]
  • A. offersDegree
    Indicates that an institution or program provides a specific academic degree as an available qualification.
  • B. offersEducationIn chosen
    Indicates that an entity provides or delivers educational programs, courses, or instruction in a specified field, subject, or area.
  • C. offersProgramsIn
    Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
  • D. offersDiscipline
    Indicates that one entity provides or makes available a particular field of study, training, or area of specialization to another entity.
  • E. offersEducationTo
    Indicates that one entity provides educational services, instruction, or learning opportunities to another entity.
  • F. None of above.

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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d89ea70819098c470344f172167 completed April 10, 2026, 9:37 p.m.
PD Predicate disambiguation batch_69d96406e97c8190b79081039847115c completed April 10, 2026, 8:56 p.m.
Created at: April 9, 2026, 5:27 p.m.