Triple

T1088472
Position Surface form Disambiguated ID Type / Status
Subject Lake Managua E24106 entity
Predicate adjacentCity P5707 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: [Lake Managua, adjacentCity, Managua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Managua
Context triple: [Lake Managua, adjacentCity, 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. 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.
  • D. 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.
  • E. Luanda
    Luanda is the capital and largest city of Angola, a major Atlantic port and economic hub with a history shaped by Portuguese colonial rule and the transatlantic slave trade.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b97d85708190a1630256648aa4a2 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c243cbc81908d6101faad628fc8 completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:42 p.m.