Triple

T1884992
Position Surface form Disambiguated ID Type / Status
Subject Borland E39942 entity
Predicate renamedAs P65 FINISHED
Object Inprise Corporation E209546 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: Inprise Corporation | Statement: [Borland, renamedAs, Inprise Corporation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inprise Corporation
Context triple: [Borland, renamedAs, Inprise Corporation]
  • A. Inprise Corporation chosen
    Inprise Corporation was the temporary name used by software company Borland during a late-1990s rebranding focused on enterprise solutions.
  • B. Syntrillium Software
    Syntrillium Software was a software company best known for creating the audio editing program Cool Edit, which later evolved into Adobe Audition after Adobe acquired the firm.
  • C. Relational Software Inc.
    Relational Software Inc. was the early name of the company that eventually became Oracle Corporation, a major multinational database and enterprise software company.
  • D. Wyatt Software
    Wyatt Software was a software company known for employing pioneering programmer Ward Cunningham early in his career.
  • E. Jasper Technologies
    Jasper Technologies is a cloud-based Internet of Things (IoT) platform provider known for enabling companies to manage and monetize connected devices and services.
  • 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_69a88633e4fc8190b7eb40463e048ec5 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb11eb2d0819088d67b1cfc772049 completed March 7, 2026, 5:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeae631488190b5b4a8137112e568 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:34 p.m.