Triple

T4486572
Position Surface form Disambiguated ID Type / Status
Subject Filbert Steps E107253 entity
Predicate hasView P854 FINISHED
Object Embarcadero E38238 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: Embarcadero | Statement: [Filbert Steps, hasView, Embarcadero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Embarcadero
Context triple: [Filbert Steps, hasView, Embarcadero]
  • A. Embarcadero chosen
    Embarcadero is a historic waterfront district in San Francisco known for its piers, ferry terminal, and scenic promenade along the bay.
  • B. Embarcadero Technologies
    Embarcadero Technologies is a software company best known for developing database tools and the Delphi rapid application development environment for Windows and cross-platform applications.
  • 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. Borland
    Borland was a prominent software company best known for its influential development tools and programming environments, particularly during the 1980s and 1990s.
  • E. Delphi (programming language)
    Delphi is an object-oriented, rapid application development programming language and environment derived from Pascal, primarily used for building native Windows applications.
  • 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_69bd43f84f788190a1383579c4a595be completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd52a958288190974b292f54a0e045 completed March 20, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd679cd3b88190a9b90f50f2b7beae completed March 20, 2026, 3:28 p.m.
Created at: March 20, 2026, 12:59 p.m.