Triple

T1304296
Position Surface form Disambiguated ID Type / Status
Subject American Convention on Human Rights E27838 entity
Predicate adoptedInCity P4186 FINISHED
Object San José E29798 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: [American Convention on Human Rights, adoptedInCity, San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San José
Context triple: [American Convention on Human Rights, adoptedInCity, San José]
  • A. San José chosen
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • B. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • C. San Fernando
    San Fernando is a Philippine city on the island of Luzon known as a regional commercial and administrative center.
  • D. San Fernando
    San Fernando is a major industrial and commercial city located in the southern part of Trinidad, known for its energy sector and bustling urban center.
  • E. San Fernando
    San Fernando is a principal urban center and agricultural hub in central Chile’s O’Higgins Region.
  • 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c13393388190b784d6bd8c447dda completed March 1, 2026, 10:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad51996dc08190afecb40095e3d3e2 completed March 8, 2026, 10:38 a.m.
Created at: March 1, 2026, 7:51 p.m.