Triple

T12754734
Position Surface form Disambiguated ID Type / Status
Subject Nokia E60 E304827 entity
Predicate userInterface P1594 FINISHED
Object S60 3rd Edition E277048 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 E60, userInterface, S60 3rd Edition]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: S60 3rd Edition
Context triple: [Nokia E60, userInterface, S60 3rd Edition]
  • A. S60 chosen
    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
    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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d89ea70819098c470344f172167 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c9aa6308190bfcb1511a561c0f9 completed May 2, 2026, 10:37 p.m.
Created at: April 9, 2026, 5:27 p.m.