Triple

T10274950
Position Surface form Disambiguated ID Type / Status
Subject Danealia Mineta E240938 entity
Predicate residence P75 FINISHED
Object San Jose, California 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, California | Statement: [Danealia Mineta, residence, San Jose, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Jose, California
Context triple: [Danealia Mineta, residence, San Jose, California]
  • A. 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.
  • B. San Jose chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • C. 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.
  • D. San Jose
    San Jose is a municipality in the province of Batangas in the Philippines, known for its agricultural economy and rural communities.
  • E. San Jose
    San Jose is a coastal municipality in the Philippine province of Romblon known for its island landscapes and fishing communities.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d28a9c508190824867c04e8dcbe7 completed April 7, 2026, 9:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69e215ac56248190a75ad5ceb8152d5a completed April 17, 2026, 11:12 a.m.
Created at: April 6, 2026, 11:37 a.m.