Triple

T5780266
Position Surface form Disambiguated ID Type / Status
Subject Gartner E127538 entity
Predicate name P16 FINISHED
Object Gartner, Inc. E127538 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: Gartner, Inc. | Statement: [Gartner, name, Gartner, Inc.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gartner, Inc.
Context triple: [Gartner, name, Gartner, Inc.]
  • A. Gartner chosen
    Gartner is a leading global research and advisory company that provides insights, advice, and tools for business and technology leaders.
  • B. Andersen Consulting
    Andersen Consulting was a major global management and technology consulting firm that later became Accenture, known for advising corporations and governments on strategy, operations, and IT.
  • C. Accenture
    Accenture is a global professional services company specializing in consulting, technology, and outsourcing solutions for businesses and governments worldwide.
  • D. 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.
  • E. Unisys
    Unisys is an American global information technology company known for providing IT services, software, and infrastructure solutions to government and commercial clients.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e3f88c8190975921ff2912e543 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e7773888190bd8c3e1d7df62f5c completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:50 p.m.