Triple

T8945794
Position Surface form Disambiguated ID Type / Status
Subject Philippe Kahn E213217 entity
Predicate founded P104 FINISHED
Object Starfish Software E768007 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: Starfish Software | Statement: [Philippe Kahn, founded, Starfish Software]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starfish Software
Context triple: [Philippe Kahn, founded, Starfish Software]
  • A. Starfish Software chosen
    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.
  • 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. Avalanche Software
    Avalanche Software is an American video game development studio best known for creating titles such as Disney Infinity and Hogwarts Legacy.
  • D. Altamira Software
    Altamira Software was a pioneering computer graphics and digital imaging company co-founded by computer graphics visionary Alvy Ray Smith.
  • E. Helionix
    Helionix is an advanced, integrated avionics system developed by Airbus Helicopters to enhance situational awareness, safety, and mission efficiency in modern rotorcraft.
  • 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_69ca839843408190a39069a029a89f15 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66dd00c481908ff20fd66c1954cc completed April 1, 2026, 12:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc93a1e4c8190b33478783dcd09d7 completed April 3, 2026, 2:05 p.m.
Created at: March 30, 2026, 6:59 p.m.