Triple

T1668735
Position Surface form Disambiguated ID Type / Status
Subject SQLite E36073 entity
Predicate usedBy P260 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: [SQLite, usedBy, Safari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Safari
Context triple: [SQLite, usedBy, 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. 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.
  • C. Mozilla Firefox
    Mozilla Firefox is a free, open-source web browser developed by Mozilla, known for its strong privacy features, customizability, and support for open web standards.
  • D. Colibri Browser
    Colibri Browser is a minimalist web browser focused on speed and simplicity, built on the Blink rendering engine.
  • E. Torch Browser
    Torch Browser is a Chromium-based web browser known for its built-in media downloading, torrent management, and social media integration features.
  • 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adf3d3c81909233e574e79b82a2 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad683207b08190a86c266aaece4e98 completed March 8, 2026, 12:14 p.m.
Created at: March 4, 2026, 7:29 p.m.