Triple

T18273748
Position Surface form Disambiguated ID Type / Status
Subject UES E437678 entity
Predicate locatedIn P40 FINISHED
Object San Salvador 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 Salvador | Statement: [UES, locatedIn, San Salvador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Salvador
Context triple: [UES, locatedIn, San Salvador]
  • A. San Salvador chosen
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • B. San Pedro Sula
    San Pedro Sula is a large industrial and commercial city in northern Honduras, historically known as the country’s economic hub.
  • C. Tegucigalpa
    Tegucigalpa is the capital and largest city of Honduras, serving as its political, cultural, and economic center.
  • D. Xcalakoop San Salvador
    Xcalakoop San Salvador is a locality within the municipality of Tinum in the Mexican state of Yucatán, known for its rural character in the Yucatán Peninsula.
  • E. Juigalpa
    Juigalpa is a city in central Nicaragua that serves as the capital of the Chontales Department and a regional hub for agriculture and cattle ranching.
  • 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_69d8b914530c8190b4474d862a2b2a1b completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5005006108190bbddddbe6bbdc911 completed April 19, 2026, 4:18 p.m.
Created at: April 10, 2026, 10:34 a.m.