Triple

T16900822
Position Surface form Disambiguated ID Type / Status
Subject Northern Honduras E424429 entity
Predicate hasPortCity P2745 FINISHED
Object Puerto Cortés E378787 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: Puerto Cortés | Statement: [Northern Honduras, hasPortCity, Puerto Cortés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Cortés
Context triple: [Northern Honduras, hasPortCity, Puerto Cortés]
  • A. Puerto Cortés chosen
    Puerto Cortés is a major Honduran Caribbean port city known as one of Central America’s busiest and most important maritime hubs.
  • B. Puerto de La Ceiba
    Puerto de La Ceiba is the main maritime port serving the coastal Honduran city of La Ceiba, handling regional passenger and cargo traffic in the Caribbean.
  • C. Puerto La Victoria
    Puerto La Victoria is a riverside town in Paraguay situated along the Paraguay River, serving as a local hub for transport and river-based commerce.
  • D. Puerto Nuevo
    Puerto Nuevo is a small lakeside settlement in southern Chile situated on the shores of Ranco Lake.
  • E. Puerto Armuelles
    Puerto Armuelles is a coastal Panamanian town on the Pacific Ocean known historically for its banana industry and port activities.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3c8dc7cf08190ad935935d8daf1d0 completed April 18, 2026, 6:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45647f481908ae76a0b8fe8a9cb completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:29 a.m.