Triple

T21375868
Position Surface form Disambiguated ID Type / Status
Subject Jen Tullock E527200 entity
Predicate employer P7 FINISHED
Object Apple TV+ NE NERFINISHED

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: Apple TV+ | Statement: [Jen Tullock, employer, Apple TV+]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apple TV+
Context triple: [Jen Tullock, employer, Apple TV+]
  • A. Apple TV+ chosen
    Apple TV+ is Apple’s subscription-based streaming platform offering original TV series, films, and documentaries across its devices and the web.
  • B. Apple TV
    Apple TV is a digital media player and streaming device by Apple that lets users watch movies, TV shows, and other content from various apps and services on their television.
  • C. Acorn TV
    Acorn TV is a subscription streaming service specializing in British and international television dramas, mysteries, and comedies.
  • D. Apple TV (macOS app)
    Apple TV (macOS app) is Apple's media application on macOS for streaming, purchasing, and organizing movies and TV shows, integrating both Apple TV+ and the user's existing video library.
  • E. Disney+
    Disney+ is a subscription-based streaming service from The Walt Disney Company that offers movies and TV shows from Disney, Pixar, Marvel, Star Wars, National Geographic, and more.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69ee5bb031988190ae587730a2131a50 completed April 26, 2026, 6:38 p.m.
Created at: April 16, 2026, 5:11 p.m.