Triple

T15095905
Position Surface form Disambiguated ID Type / Status
Subject Greg Maffei E360535 entity
Predicate boardMemberOf P10 FINISHED
Object Citrix Systems E724332 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: Citrix Systems | Statement: [Greg Maffei, boardMemberOf, Citrix Systems]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Citrix Systems
Context triple: [Greg Maffei, boardMemberOf, Citrix Systems]
  • A. Citrix Systems chosen
    Citrix Systems is an American software company best known for its virtualization, remote access, and cloud computing technologies that enable secure delivery of applications and desktops.
  • B. Nutanix
    Nutanix is a cloud computing company best known for pioneering hyper-converged infrastructure software that simplifies data center and multicloud operations.
  • C. Hewlett Packard Enterprise
    Hewlett Packard Enterprise is a major American multinational enterprise IT company that provides servers, storage, networking, and related services to business and government customers worldwide.
  • D. CA Technologies
    CA Technologies was a major American enterprise software company known for its mainframe, IT management, and security solutions before being acquired by Broadcom.
  • E. Azul Systems
    Azul Systems is a software company specializing in high-performance, scalable Java runtimes and JVM technologies for enterprise applications.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e005466e9c8190a68e1fbeb8922b1a completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae21134c81908939ad6ce46703d8 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:04 a.m.