Triple

T55495
Position Surface form Disambiguated ID Type / Status
Subject Google E1096 entity
Predicate product P490 FINISHED
Object Wear OS
Wear OS is Google’s smartwatch operating system designed to bring Android apps, notifications, and Google services to wearable devices.
 E2486 NE FINISHED

How this triple was built (4 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: Wear OS | Statement: [Google, product, Wear OS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wear OS
Context triple: [Google, product, Wear OS]
  • A. Ventra
    Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
  • B. NFC
    The NFC (National Football Conference) is one of the two conferences in the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • D. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • E. WAI
    WAI (Web Accessibility Initiative) is a World Wide Web Consortium (W3C) program that develops guidelines, resources, and standards to make the web accessible to people with disabilities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wear OS
Triple: [Google, product, Wear OS]
Generated description
Wear OS is Google’s smartwatch operating system designed to bring Android apps, notifications, and Google services to wearable devices.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wear OS
Target entity description: Wear OS is Google’s smartwatch operating system designed to bring Android apps, notifications, and Google services to wearable devices.
  • A. Ventra
    Ventra is the contactless fare payment system used across Chicago’s public transit network, including buses and trains.
  • B. NFC
    The NFC (National Football Conference) is one of the two conferences in the National Football League, comprising 16 teams that compete for a spot in the Super Bowl.
  • C. WAS
    WAS is the standard three-letter abbreviation used for the Washington Commanders NFL franchise.
  • D. WAS
    WAS is the station code for Washington, D.C.’s main intercity and commuter rail hub, Union Station.
  • E. WAI
    WAI (Web Accessibility Initiative) is a World Wide Web Consortium (W3C) program that develops guidelines, resources, and standards to make the web accessible to people with disabilities.
  • F. None of above. chosen

Provenance (5 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.
NEDg Description generation batch_69a24f001c588190b7eec6eec4fb5fd9 completed Feb. 28, 2026, 2:12 a.m.
NED2 Entity disambiguation (via description) batch_69a24fcbeee4819087186dada7466dfe completed Feb. 28, 2026, 2:15 a.m.
Created at: Feb. 28, 2026, 1:50 a.m.