Triple

T400891
Position Surface form Disambiguated ID Type / Status
Subject CTO of Opera Software E9277 entity
Predicate employer P7 FINISHED
Object Opera Software E9276 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 Software | Statement: [CTO of Opera Software, employer, Opera Software]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Opera Software
Context triple: [CTO of Opera Software, employer, Opera Software]
  • A. Opera Software chosen
    Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
  • B. Netscape Communications Corporation
    Netscape Communications Corporation was a pioneering web browser company of the 1990s whose Netscape Navigator played a central role in the early popularization of the World Wide Web.
  • C. Micros Systems
    Micros Systems was a leading provider of point-of-sale and hospitality management software and hardware solutions for restaurants, hotels, and retail businesses.
  • D. Microsoft
    Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
  • E. Embarcadero
    Embarcadero is a historic waterfront district in San Francisco known for its piers, ferry terminal, and scenic promenade along the bay.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec8e655c819081eff85c0ef55fa5 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a410410c108190990d4d5ef2e7ff61 completed March 1, 2026, 10:09 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.