Triple

T9502624
Position Surface form Disambiguated ID Type / Status
Subject macOS Monterey E229180 entity
Predicate includedApplication P1393 FINISHED
Object Safari E95180 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: Safari | Statement: [macOS Monterey, includedApplication, Safari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Safari
Context triple: [macOS Monterey, includedApplication, Safari]
  • A. Safari chosen
    Safari is Apple’s native web browser for macOS and iOS, known for its speed, energy efficiency, and deep integration with the Apple ecosystem.
  • B. Safari
    "Safari" is a reggaeton song by Colombian artist J Balvin, known for its infectious rhythm and international popularity.
  • C. Safari
    "Safari" is an alternative rock song by American band The Breeders, known for its fuzzy guitars, dynamic shifts, and early-1990s indie sound.
  • D. Silk Browser
    Silk Browser is Amazon's cloud-accelerated web browser designed primarily for use on Fire tablets and other Amazon devices.
  • E. Kinza Browser
    Kinza Browser is a Japanese-developed, Chromium-based web browser that offers extensive customization options and user-centric features built on the Blink rendering engine.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd983ea6048190a2d7924c8e6d1fbc completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a10f7b08190b8e4d4bc3b9815c6 completed April 4, 2026, 4:19 p.m.
Created at: March 30, 2026, 7:57 p.m.