Triple

T15475385
Position Surface form Disambiguated ID Type / Status
Subject Oakland Estuary E376769 entity
Predicate separates P1175 FINISHED
Object City of Alameda E1088902 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: City of Alameda | Statement: [Oakland Estuary, separates, City of Alameda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Alameda
Context triple: [Oakland Estuary, separates, City of Alameda]
  • A. City of Alameda chosen
    The City of Alameda is a Bay Area island municipality in California known for its historic Victorian architecture, waterfront neighborhoods, and proximity to San Francisco.
  • B. Alameda
    Alameda is a major Lisbon metro and transport hub that serves as a key interchange point within the city's public transit network.
  • C. Alameda
    Alameda is the main central avenue of Santiago, Chile, serving as a key thoroughfare and symbolic axis of the city.
  • D. City of San Pablo
    The City of San Pablo is a small, historically working-class municipality in Contra Costa County, California, located in the East Bay region just north of Richmond.
  • E. City of Pacifica
    The City of Pacifica is a coastal municipality in San Mateo County, California, known for its scenic beaches, rugged bluffs, and popular surfing spots just south of San Francisco.
  • 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.