Triple

T8806366
Position Surface form Disambiguated ID Type / Status
Subject C++Builder E209541 entity
Predicate usesFramework P1587 FINISHED
Object FireMonkey E62593 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: FireMonkey | Statement: [C++Builder, usesFramework, FireMonkey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: FireMonkey
Context triple: [C++Builder, usesFramework, FireMonkey]
  • A. FMX chosen
    FMX (FireMonkey) is a cross-platform application development framework used in Delphi for building native GUI applications on Windows, macOS, iOS, and Android.
  • B. DELPHI
    DELPHI was a major particle physics detector experiment at CERN’s Large Electron–Positron Collider that studied high-energy electron–positron collisions to test the Standard Model and search for new phenomena.
  • C. Delphi
    Delphi is an ancient Greek sanctuary and archaeological site famed for the Oracle of Apollo and its central role in classical Greek religion and culture.
  • D. Delphi
    Delphi is a central antagonist in the stage play "Harry Potter and the Cursed Child," portrayed as a mysterious young witch with a powerful and dangerous connection to Voldemort.
  • E. Embarcadero
    Embarcadero is a historic waterfront district in San Francisco known for its piers, ferry terminal, and scenic promenade along the bay.
  • 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_69ca836320e48190b5cf585b90a322c4 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fd1f1a08190a2e584f6b0495f5c completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf8921a13081909346b97c024110b6 completed April 3, 2026, 9:32 a.m.
Created at: March 30, 2026, 6:45 p.m.