Triple

T2272420
Position Surface form Disambiguated ID Type / Status
Subject Fargo, North Dakota E50689 entity
Predicate majorEmployer P588 FINISHED
Object Microsoft E1649 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: Microsoft | Statement: [Fargo, North Dakota, majorEmployer, Microsoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft
Context triple: [Fargo, North Dakota, majorEmployer, Microsoft]
  • A. Microsoft chosen
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • B. Micros Systems
    Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
  • C. Microsoft Office
    Microsoft Office is a widely used suite of productivity applications developed by Microsoft, including programs for word processing, spreadsheets, presentations, email, and more.
  • D. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • E. Microsoft Mobile
    Microsoft Mobile was the Microsoft-owned division responsible for designing, manufacturing, and marketing Lumia smartphones and other mobile devices following the acquisition of Nokia’s handset business.
  • 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_69a88b05910c8190a9a2b1ff230c85f9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc1e872448190a1d6c6071b2a294b completed March 7, 2026, 6:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae71db927c8190a76cfb873039b04b completed March 9, 2026, 7:08 a.m.
Created at: March 4, 2026, 7:48 p.m.