Triple

T15862923
Position Surface form Disambiguated ID Type / Status
Subject Anthony Wood E384635 entity
Predicate associatedWith P37 FINISHED
Object Roku OS E72793 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: Roku OS | Statement: [Anthony Wood, associatedWith, Roku OS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roku OS
Context triple: [Anthony Wood, associatedWith, Roku OS]
  • A. Roku chosen
    Roku is a popular digital media player platform that streams internet-based television, movies, and other content through apps and channels on connected TVs.
  • B. Kodi
    Kodi is the given name of Australian actor Kodi Smit-McPhee, known for roles in films such as "The Power of the Dog" and the "X-Men" series.
  • C. Fire OS
    Fire OS is Amazon's Android-based operating system designed primarily for its Fire tablets, Fire TV devices, and other Amazon hardware.
  • D. Tizen
    Tizen is a Linux-based open-source operating system primarily used in smart TVs, wearables, and other embedded and IoT devices.
  • E. KaiOS
    KaiOS is a lightweight mobile operating system designed for feature phones, bringing smartphone-like apps and internet capabilities to devices with limited hardware.
  • 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_69d86da422088190aac39e32e6c68429 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1555d38fc8190bd8820bb5b238b71 completed April 16, 2026, 9:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa9439db481908be2f6d8a3cfbc85 completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:50 a.m.