Triple

T925698
Position Surface form Disambiguated ID Type / Status
Subject Solano County E19977 entity
Predicate containsCity P294 FINISHED
Object Vallejo E28332 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: Vallejo | Statement: [Solano County, containsCity, Vallejo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vallejo
Context triple: [Solano County, containsCity, Vallejo]
  • A. Vallejo chosen
    Vallejo is a waterfront city in the San Francisco Bay Area known for its former Mare Island Naval Shipyard and diverse, working-class community.
  • B. Santa Cruz
    Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
  • C. Sausalito
    Sausalito is a picturesque waterfront city in Northern California known for its hillside homes, art galleries, and views of the San Francisco Bay.
  • D. Salinas
    Salinas is a prominent agricultural city in Northern California, often called the "Salad Bowl of the World" and known as the birthplace of author John Steinbeck.
  • E. Monterey
    Monterey is a small rural town in Berkshire County, western Massachusetts, known for its scenic landscapes, forests, and lakes.
  • 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_69a493a099788190a696d9d8408cbaf4 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b32ad9f88190b7d477d0a9a9dbc8 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad606f1c008190adca6fa6f0d6cd66 completed March 8, 2026, 11:41 a.m.
Created at: March 1, 2026, 7:40 p.m.