Triple

T18138844
Position Surface form Disambiguated ID Type / Status
Subject Sixten Sason E434207 entity
Predicate employer P7 FINISHED
Object Saab NE NERFINISHED

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: Saab | Statement: [Sixten Sason, employer, Saab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saab
Context triple: [Sixten Sason, employer, Saab]
  • A. Saab Automobile
    Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
  • B. Saab Kockums
    Saab Kockums is a Swedish shipyard and defense company best known for designing and building advanced submarines and naval vessels.
  • C. Saab AB chosen
    Saab AB is a Swedish aerospace and defense company known for developing military aircraft, advanced defense systems, and security solutions.
  • D. Saab 600
    The Saab 600 was a rebadged version of the first-generation Lancia Delta hatchback, sold by Saab primarily in Nordic markets in the early 1980s.
  • E. Saab 96
    The Saab 96 is a compact Swedish car produced from 1960 to 1980, known for its distinctive aerodynamic shape, front-wheel drive, and success in international rallying.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de0993e88190b19c5cb35a6d252d completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.