Triple

T13311148
Position Surface form Disambiguated ID Type / Status
Subject Belmont Caltrain station E317066 entity
Predicate between P1262 FINISHED
Object San Jose E1776 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: San Jose | Statement: [Belmont Caltrain station, between, San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose
Context triple: [Belmont Caltrain station, between, 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 chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • D. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • E. San Jose
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f56abc8190951774a999e2ce11 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8bcbb34819088c21d79357eef8a completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:29 p.m.