Triple

T11946558
Position Surface form Disambiguated ID Type / Status
Subject Mach microkernel E284313 entity
Predicate developer P73 FINISHED
Object Carnegie Mellon University E33793 NE 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: Carnegie Mellon University | Statement: [Mach microkernel, developer, Carnegie Mellon University]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carnegie Mellon University
Context triple: [Mach microkernel, developer, Carnegie Mellon University]
  • A. CMU
    CMU is a public university in Grand Junction, Colorado, known for its diverse undergraduate programs and strong regional presence on the Western Slope.
  • B. CMU
    CMU is a major medical university located in Shenyang, China, known for its education and research in clinical medicine and related health sciences.
  • C. 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.
  • D. CMU chosen
    CMU is a private research university in Pittsburgh, Pennsylvania, renowned for its leading programs in computer science, engineering, and the arts.
  • 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 (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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903456ec0819082b8b10755a6b732 completed April 10, 2026, 2:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f458cbb08881909a71f0592c9231ae completed May 1, 2026, 7:39 a.m.
Created at: April 8, 2026, 9:45 p.m.