Triple

T8114006
Position Surface form Disambiguated ID Type / Status
Subject Sasebo E189425 entity
Predicate sisterCity P1072 FINISHED
Object Alameda, California E180395 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: Alameda, California | Statement: [Sasebo, sisterCity, Alameda, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alameda, California
Context triple: [Sasebo, sisterCity, Alameda, California]
  • A. Alameda, California chosen
    Alameda, California is a Bay Area island city adjacent to Oakland known for its historic Victorian architecture, waterfront parks, and residential neighborhoods.
  • 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. Emeryville, California
    Emeryville, California is a small city in the San Francisco Bay Area best known as the longtime home of Pixar Animation Studios and a hub for tech and creative industries.
  • E. Oakland
    Oakland is a major port city in the San Francisco Bay Area known for its cultural diversity, progressive politics, and significant role in West Coast shipping and industry.
  • 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_69ca82baad008190ab2859712b9b1607 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb432f2a24819097be6ab9b03567bd completed March 31, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd948fcf90819090c80e1ac4ac1b0c completed April 1, 2026, 9:56 p.m.
Created at: March 30, 2026, 5:32 p.m.