Triple

T343134
Position Surface form Disambiguated ID Type / Status
Subject Financial District (San Francisco) E6880 entity
Predicate adjacentTo P224 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: [Financial District (San Francisco), adjacentTo, Embarcadero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Embarcadero
Context triple: [Financial District (San Francisco), adjacentTo, 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. 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.
  • C. Borland
    Borland was a prominent software company best known for its influential development tools and programming environments, particularly during the 1980s and 1990s.
  • D. 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.
  • E. Tableau
    Tableau is a widely used data visualization and business intelligence software platform that enables users to analyze, explore, and present data through interactive dashboards and reports.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb0019088190a9b969c4287dc4fa completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3d4ea324c8190acd07727ca0ac193 completed March 1, 2026, 5:55 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.