Triple

T14842720
Position Surface form Disambiguated ID Type / Status
Subject School of Languages, Cultures, and World Affairs E349004 entity
Predicate typicalDepartmentsInclude P85516 FINISHED
Object foreign language departments 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: foreign language departments | Statement: [School of Languages, Cultures, and World Affairs, typicalDepartmentsInclude, foreign language departments]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typicalDepartmentsInclude
Context triple: [School of Languages, Cultures, and World Affairs, typicalDepartmentsInclude, foreign language departments]
  • A. commonDepartments
    Indicates that two or more entities share one or more of the same departments in common.
  • B. typicalOccupationsInclude
    Indicates that the usual or commonly associated jobs or professions for an entity include the specified occupation(s).
  • C. departmentType
    Indicates the classification or category of a department, specifying what kind of department it is.
  • D. coversDepartment chosen
    Indicates that one entity includes, encompasses, or has responsibility for a particular department within its scope.
  • E. recognizesDepartment
    Indicates that one entity formally acknowledges or accepts another entity as a valid or official department.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28fa49c81908d1059e6cafd607f completed April 14, 2026, 11:49 p.m.
PD Predicate disambiguation batch_69de8c13418c819088ff9905ace1416a completed April 14, 2026, 6:48 p.m.
Created at: April 10, 2026, 1:53 a.m.