Triple

T14439223
Position Surface form Disambiguated ID Type / Status
Subject PVCS E358043 entity
Predicate laterOwnedBy P22682 FINISHED
Object Serena Software E759389 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: Serena Software | Statement: [PVCS, laterOwnedBy, Serena Software]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Serena Software
Context triple: [PVCS, laterOwnedBy, Serena Software]
  • A. Serena Software chosen
    Serena Software is an enterprise software company best known for its application lifecycle management and DevOps solutions for large organizations.
  • 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. Altamira Software
    Altamira Software was a pioneering computer graphics and digital imaging company co-founded by computer graphics visionary Alvy Ray Smith.
  • D. Starfish Software
    Starfish Software was a software company co-founded by tech entrepreneur Philippe Kahn, best known for its work in wireless synchronization and mobile data management solutions in the 1990s.
  • E. Rockwell Software
    Rockwell Software is a business unit of Rockwell Automation that develops industrial automation and manufacturing execution system (MES) software solutions.
  • 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_69d8279402a88190821ffa39ae15bccf completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de914a45ec81909ab8ccf302047d7f completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bd7f46881908df1a1cea7b6af9b completed May 8, 2026, 3:43 a.m.
Created at: April 10, 2026, 1:18 a.m.