Triple

T18248618
Position Surface form Disambiguated ID Type / Status
Subject San Francisco Bay Trail E437021 entity
Predicate passesThrough P225 FINISHED
Object San Jose — 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 Jose | Statement: [San Francisco Bay Trail, passesThrough, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose
Context triple: [San Francisco Bay Trail, passesThrough, San Jose]
  • A. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • B. San Jose
    San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
  • C. San Jose
    San Jose is a city in Bulacan, Philippines, officially known as San Jose del Monte and commonly referred to by its shortened nickname.
  • D. San Jose
    San Jose is a coastal municipality in the province of Occidental Mindoro in the Philippines, known as a commercial and transportation hub for the region.
  • E. San Jose chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4fd7fa3708190baefd8d938d20807 completed April 19, 2026, 4:06 p.m.
Created at: April 10, 2026, 10:33 a.m.