Triple

T5718824
Position Surface form Disambiguated ID Type / Status
Subject Lago Xolotlán E126088 entity
Predicate hasNearbyCity P350 FINISHED
Object Managua E17545 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: Managua | Statement: [Lago Xolotlán, hasNearbyCity, Managua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Managua
Context triple: [Lago Xolotlán, hasNearbyCity, Managua]
  • A. Managua chosen
    Managua is the capital and largest city of Nicaragua, located on the southwestern shore of Lake Managua in Central America.
  • B. Malabo
    Malabo is the largest city and main economic and administrative center of Equatorial Guinea, located on the northern coast of Bioko Island in the Gulf of Guinea.
  • C. Bangui
    Bangui is the capital and largest city of the Central African Republic, serving as its political, economic, and cultural 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. Estelí
    Estelí is a city in northern Nicaragua known for its tobacco production, cigar industry, and role as a commercial and cultural center in the 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e1ec7c8190a08e1b7954db2a9d completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097ebde448190806bb5bc7a2096fc completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:46 p.m.