Triple

T10533005
Position Surface form Disambiguated ID Type / Status
Subject Rincon Hill E248490 entity
Predicate locatedNear P294 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: [Rincon Hill, locatedNear, Embarcadero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Embarcadero
Context triple: [Rincon Hill, locatedNear, 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 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.
  • D. 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.
  • 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_69d381c5c7448190bec34bee7ec72bac completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a19b59c8190b00db7d5813ad37d completed April 7, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9340da2948190950e7c0ceea12cb1 completed April 10, 2026, 5:31 p.m.
Created at: April 6, 2026, 12:30 p.m.