Triple

T18204346
Position Surface form Disambiguated ID Type / Status
Subject XLNet E435866 entity
Predicate developedBy P73 FINISHED
Object Carnegie Mellon University NE NERFINISHED

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: Carnegie Mellon University | Statement: [XLNet, developedBy, Carnegie Mellon University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carnegie Mellon University
Context triple: [XLNet, developedBy, Carnegie Mellon University]
  • A. CMU chosen
    CMU is a private research university in Pittsburgh, Pennsylvania, renowned for its leading programs in computer science, engineering, and the arts.
  • B. CMU
    CMU is a public university in Grand Junction, Colorado, known for its diverse undergraduate programs and strong regional presence on the Western Slope.
  • C. CMU
    CMU is a major medical university located in Shenyang, China, known for its education and research in clinical medicine and related health sciences.
  • D. CMU
    CMU is a major public research university in Chiang Mai, Thailand, known for its comprehensive academic programs and role as a leading educational institution in northern Thailand.
  • E. University of Pittsburgh
    The University of Pittsburgh is a major public research university in Pittsburgh, Pennsylvania, known for its strong programs in medicine, engineering, and the liberal arts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.