Triple

T2501765
Position Surface form Disambiguated ID Type / Status
Subject Government of El Salvador E52480 entity
Predicate seatOfGovernment P761 FINISHED
Object San Salvador E15340 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 Salvador | Statement: [Government of El Salvador, seatOfGovernment, San Salvador]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Salvador
Context triple: [Government of El Salvador, seatOfGovernment, 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. 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.
  • E. Guatemala City
    Guatemala City is the capital and largest city of Guatemala, serving as the country’s political, economic, and cultural center.
  • 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_69ab4957b3a88190adf968ae0c1b931c completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd1c9f80c8190b40ada396e184e75 completed March 7, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2b8bc7708190a507136d1f9f34ca completed March 9, 2026, 8:20 p.m.
Created at: March 6, 2026, 9:46 p.m.