Triple

T9317853
Position Surface form Disambiguated ID Type / Status
Subject macOS Big Sur E224167 entity
Predicate includesApplication P14571 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 Big Sur, includesApplication, Safari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Safari
Context triple: [macOS Big Sur, includesApplication, 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_69ca8425f4fc81909c1c586e9a5b7530 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358b66148190a918c107490c8406 completed April 1, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0c7b73ff881909e936374fd90a822 completed April 4, 2026, 8:11 a.m.
Created at: March 30, 2026, 7:38 p.m.