Triple

T5553373
Position Surface form Disambiguated ID Type / Status
Subject Chinandega Department E145579 entity
Predicate largestCity P235 FINISHED
Object Chinandega E424376 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: Chinandega | Statement: [Chinandega Department, largestCity, Chinandega]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chinandega
Context triple: [Chinandega Department, largestCity, Chinandega]
  • A. Chinandega chosen
    Chinandega is a city in northwestern Nicaragua known as a commercial and agricultural hub near the country’s highest volcanoes.
  • B. Cochamó
    Cochamó is a rural commune and village in Chile’s Los Lagos Region, known for its dramatic granite valleys, lush temperate rainforests, and outdoor recreation such as trekking and rock climbing.
  • C. Huambisa
    Huambisa is an indigenous Jivaroan language spoken by the Huambisa people of the northern Peruvian Amazon.
  • D. Caxangá
    Caxangá is a neighborhood and important urban area within the city of Recife, Brazil.
  • E. El Chal
    El Chal is a municipality and town located in Guatemala's northern Petén region, known for its rural communities and proximity to Maya archaeological areas.
  • 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_69c008fcaf788190bafa02a1917ee73b completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01ff9c9c48190b5e587d58c6515d8 completed March 22, 2026, 4:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097b96f708190a40b67e32e4b4b47 completed March 23, 2026, 1:30 a.m.
Created at: March 22, 2026, 3:35 p.m.