Triple

T20976109
Position Surface form Disambiguated ID Type / Status
Subject Marin Transit E516629 entity
Predicate headquartersLocation P62 FINISHED
Object San Rafael, California 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: San Rafael, California | Statement: [Marin Transit, headquartersLocation, San Rafael, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Rafael, California
Context triple: [Marin Transit, headquartersLocation, San Rafael, California]
  • A. San Rafael
    San Rafael is a barangay (village-level administrative division) within the municipality of San Antonio in the province of Zambales, Philippines.
  • B. San Rafael
    San Rafael is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and growing suburban communities.
  • C. San Rafael chosen
    San Rafael is a city in the North Bay region of the San Francisco Bay Area in California, known for its historic downtown and role as a cultural and economic hub of Marin County.
  • D. San Rafael
    San Rafael is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
  • E. San Rafael
    San Rafael is a rural barangay of the municipality of Botolan in the province of Zambales, Philippines.
  • 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fba3df2081908c1db5f8610ba43d completed April 21, 2026, 4:23 a.m.
Created at: April 16, 2026, 1:47 p.m.