Triple

T5613368
Position Surface form Disambiguated ID Type / Status
Subject DigiPen Institute of Technology E147415 entity
Predicate collaboratesWith P37 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: [DigiPen Institute of Technology, collaboratesWith, Microsoft]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Microsoft
Context triple: [DigiPen Institute of Technology, collaboratesWith, 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. WIN Corporation
    WIN Corporation is an Australian media company best known for owning and operating the WIN Television network and related broadcasting assets.
  • D. 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.
  • E. IBM
    IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c021226cf88190b70b4b51eb5b4144 completed March 22, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027a10fa08190853d45354fd9b044 completed March 22, 2026, 5:32 p.m.
Created at: March 22, 2026, 3:39 p.m.