Triple

T55490
Position Surface form Disambiguated ID Type / Status
Subject Google E1096 entity
Predicate product P490 FINISHED
Object Google Docs Editors suite E1096 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: Google Docs Editors suite | Statement: [Google, product, Google Docs Editors suite]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Google Docs Editors suite
Context triple: [Google, product, Google Docs Editors suite]
  • A. Google chosen
    Google is a multinational technology company best known for its search engine and wide range of internet-related products and services, including Android, YouTube, and cloud computing.
  • B. docuverse
    Docuverse is Ted Nelson’s visionary concept of a universal, interconnected digital library where all documents are permanently linked and traceable across a global hypertext system.
  • C. Microsoft
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • D. Works Progress Administration
    The Works Progress Administration was a New Deal agency that provided millions of jobs during the Great Depression by funding public works and arts projects across the United States.
  • E. One Laptop per Child
    One Laptop per Child is an educational nonprofit initiative that aimed to provide low-cost, durable laptops to children in developing countries to support digital learning and bridge the global digital divide.
  • 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_69a248adc5b48190aa8db9fb092fb28a completed Feb. 28, 2026, 1:45 a.m.
NER Named-entity recognition batch_69a24b06c5488190afb5429a7999e3f3 completed Feb. 28, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69a24e67187c8190950aec5d9f8ecc60 completed Feb. 28, 2026, 2:09 a.m.
Created at: Feb. 28, 2026, 1:50 a.m.