Triple

T14906072
Position Surface form Disambiguated ID Type / Status
Subject Nokia N93 E360133 entity
Predicate userInterface P1594 FINISHED
Object S60 3rd Edition E277053 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: S60 3rd Edition | Statement: [Nokia N93, userInterface, S60 3rd Edition]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S60 3rd Edition
Context triple: [Nokia N93, userInterface, S60 3rd Edition]
  • A. S60
    S60 is a Symbian-based mobile software platform and user interface used primarily on Nokia smartphones in the 2000s.
  • B. S60
    S60 is a commuter rail line within the Stuttgart S-Bahn network in Germany, providing regional passenger service between suburban areas and the city.
  • C. Volvo S60
    The Volvo S60 is a compact executive sedan known for its Scandinavian design, strong safety features, and comfortable, refined driving experience.
  • D. Series 60 chosen
    Series 60 is a mobile phone software platform and user interface developed by Nokia for its Symbian-based smartphones.
  • E. Saab 9-3
    The Saab 9-3 is a compact executive car produced by Swedish automaker Saab, known for its turbocharged performance, safety features, and distinctive Scandinavian design.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded60cd5588190b1efecc2b220da69 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72b7640c8190b463f69fb67fd30a completed May 8, 2026, 11:33 p.m.
Created at: April 10, 2026, 2:12 a.m.