Triple

T6639117
Position Surface form Disambiguated ID Type / Status
Subject College of Education (San José State University) E150538 entity
Predicate city P40 FINISHED
Object San José 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 José | Statement: [College of Education (San José State University), city, San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San José
Context triple: [College of Education (San José State University), city, San José]
  • A. San José
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • B. San José
    San José is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing rural landscape in the Andean region.
  • C. San Jose City
    San Jose City is a landlocked component city in the province of Nueva Ecija in the Philippines, known as an agricultural and commercial hub in Central Luzon.
  • D. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • 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 (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_69c687f0ceb08190bf40807bfc605fa5 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff1fe8081908c32db341b0fb354 completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e455edb88190983f74f39e55665c completed March 27, 2026, 8:11 p.m.
Created at: March 27, 2026, 2 p.m.