Triple

T20718964
Position Surface form Disambiguated ID Type / Status
Subject Ulúa River E509255 entity
Predicate nearCity P350 FINISHED
Object Puerto Cortés NE NERFINISHED

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: [Ulúa River, nearCity, Puerto Cortés]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Puerto Cortés
Context triple: [Ulúa River, nearCity, 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 (2 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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1d39bec8190b3642b0d6d833375 completed April 21, 2026, 12:16 a.m.
Created at: April 16, 2026, 12:26 p.m.