Triple

T19589491
Position Surface form Disambiguated ID Type / Status
Subject La Libertad Department E470192 entity
Predicate contains P35 FINISHED
Object San Matías 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 Matías | Statement: [La Libertad Department, contains, San Matías]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Matías
Context triple: [La Libertad Department, contains, San Matías]
  • A. San Matías chosen
    San Matías is a municipality in the La Libertad department of El Salvador, known as a small rural town within the central region of the country.
  • B. Ríos Rosas
    Ríos Rosas is a Madrid Metro station located in the Chamberí district, serving as part of the city's historic Line 1.
  • C. Rio de la Paz
    Rio de la Paz is the historical Spanish name for the Peace River, a significant waterway flowing through central and southwest Florida.
  • D. Puerto Pilcomayo
    Puerto Pilcomayo is a small river port settlement in northern Argentina located on the banks of the Paraguay River, serving as a local hub for cross-border trade and transport.
  • E. Río Grande de Santiago
    Río Grande de Santiago is a major river in western Mexico that drains Lake Chapala and flows toward the Pacific, supporting regional agriculture, industry, and hydroelectric power.
  • 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_69d8e510024481908415c0d616fa6186 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64054299481908d83c85cefdab075 completed April 20, 2026, 3:03 p.m.
Created at: April 10, 2026, 1:43 p.m.