Triple

T21436474
Position Surface form Disambiguated ID Type / Status
Subject Santa Catalina School E528825 entity
Predicate city P40 FINISHED
Object Monterey NE NERFINISHED

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: Monterey | Statement: [Santa Catalina School, city, Monterey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monterey
Context triple: [Santa Catalina School, city, Monterey]
  • A. Monterey chosen
    Monterey is a historic coastal city in Northern California known for its scenic bay, marine life, and former prominence as a sardine-canning and fishing center.
  • B. Monterey
    Monterey is a small rural town in Berkshire County, western Massachusetts, known for its scenic landscapes, forests, and lakes.
  • C. San Luis Obispo
    San Luis Obispo is a small coastal city in California known for its historic downtown, nearby beaches and wineries, and its location along the scenic Highway 1 between Los Angeles and San Francisco.
  • D. Santa Barbara
    Santa Barbara is a picturesque coastal city in California known for its Mediterranean climate, red-tile roofs, and distinctive Spanish Colonial Revival architecture.
  • E. Santa Barbara
    Santa Barbara is a historic inland municipality in Iloilo province in the Philippines, known for its role in the Philippine Revolution and its well-preserved heritage sites.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c4569fa081908101baa24f8745db completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e8b537f39081909220577618657805 completed April 22, 2026, 11:47 a.m.
Created at: April 16, 2026, 6:03 p.m.