Triple

T11537
Position Surface form Disambiguated ID Type / Status
Subject Carnegie Mellon University E235 entity
Predicate hasResearchArea P934 FINISHED
Object artificial intelligence 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: artificial intelligence | Statement: [Carnegie Mellon University, hasResearchArea, artificial intelligence]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasResearchArea
Context triple: [Carnegie Mellon University, hasResearchArea, artificial intelligence]
  • A. researchStrength
    Indicates the degree to which an entity possesses strong capabilities, performance, or impact in conducting research.
  • B. hasAcademicAffiliation
    Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
  • C. hasFaculty
    Indicates that an institution or department possesses or is associated with one or more faculty members.
  • D. hasAcademicStaff
    Indicates that an institution or organization employs or is associated with one or more academic staff members.
  • E. hasAcademicRank
    Indicates that an entity holds a specific academic rank or title within an educational or research institution.
  • F. None of above. chosen

Provenance (4 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_69a23d7ad88c8190bffe8ab091d86642 completed Feb. 28, 2026, 12:57 a.m.
NER Named-entity recognition batch_69a241ea1ea081908e8a81ca97531ba5 completed Feb. 28, 2026, 1:16 a.m.
PD Predicate disambiguation batch_69a23fe7da8c8190aea795b62cb91621 completed Feb. 28, 2026, 1:07 a.m.
PDg Predicate description generation batch_69a241e933288190b02ef5369f7b8834 completed Feb. 28, 2026, 1:16 a.m.
Created at: Feb. 28, 2026, 1:02 a.m.