Triple

T2321083
Position Surface form Disambiguated ID Type / Status
Subject Matthew Garrett E51180 entity
Predicate hasEmployer P7 FINISHED
Object Red Hat E5668 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: Red Hat | Statement: [Matthew Garrett, hasEmployer, Red Hat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Hat
Context triple: [Matthew Garrett, hasEmployer, Red Hat]
  • A. Red Hat chosen
    Red Hat is a leading American open-source software company best known for its enterprise Linux distribution and related cloud and middleware solutions.
  • B. Red Hat Enterprise Linux
    Red Hat Enterprise Linux is a commercially supported, enterprise-grade Linux distribution widely used for servers, cloud deployments, and mission-critical applications.
  • C. SUSE
    SUSE is a German-based open-source software company best known for its enterprise Linux distributions and related infrastructure solutions.
  • D. Novell
    Novell was a prominent software company best known for its NetWare network operating system and contributions to enterprise networking and Linux technologies.
  • E. Fedora
    Fedora is a 1978 drama film by Billy Wilder that explores the tragic mystique and hidden costs of Hollywood stardom.
  • 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_69a88b074b908190ae983dbca7757d88 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc632474c8190972b4611a3a4ff8f completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae896911908190b53954dbf854cc18 completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:49 p.m.