Triple

T15475443
Position Surface form Disambiguated ID Type / Status
Subject Oakland Embarcadero roadway E376770 entity
Predicate hasName P744 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: [Oakland Embarcadero roadway, hasName, Embarcadero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Embarcadero
Context triple: [Oakland Embarcadero roadway, hasName, 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. 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. Borland
    Borland was a prominent software company best known for its influential development tools and programming environments, particularly during the 1980s and 1990s.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f6e859481909c3d08343b7ad27c completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d093ccc8190aefc355a837c83f4 completed May 9, 2026, 12:48 p.m.
Created at: April 10, 2026, 3:34 a.m.