Triple

T3420156
Position Surface form Disambiguated ID Type / Status
Subject Opera E72095 entity
Predicate hasVariant P455 FINISHED
Object Opera Mini E50829 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: Opera Mini | Statement: [Opera, hasVariant, Opera Mini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opera Mini
Context triple: [Opera, hasVariant, Opera Mini]
  • A. Opera Mini chosen
    Opera Mini is a lightweight mobile web browser designed to compress data and load pages quickly, especially on slower networks and lower-end devices.
  • B. Opera Mobile
    Opera Mobile is a mobile web browser developed by Opera Software, known for its speed, data compression, and support for advanced web standards on smartphones and tablets.
  • C. UR Browser
    UR Browser is a Chromium-based web browser focused on user privacy, security, and customization features.
  • D. Colibri Browser
    Colibri Browser is a minimalist web browser focused on speed and simplicity, built on the Blink rendering engine.
  • 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_69ad85ad38e48190b7660c5118a35289 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb94eb9e8819087a525df4550914b completed March 8, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69b354701e908190a8a7f14ae578fa5d completed March 13, 2026, 12:04 a.m.
Created at: March 8, 2026, 3:15 p.m.