Triple

T13081940
Position Surface form Disambiguated ID Type / Status
Subject Ligua River E310228 entity
Predicate hasNameInLanguage P15 FINISHED
Object Río Ligua E310228 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: Río Ligua | Statement: [Ligua River, hasNameInLanguage, Río Ligua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Río Ligua
Context triple: [Ligua River, hasNameInLanguage, Río Ligua]
  • A. Ligua River chosen
    The Ligua River is a river in central Chile that flows through the Petorca Province toward the Pacific Ocean, supporting local agriculture and settlements along its course.
  • B. Guareña River
    The Guareña River is a tributary watercourse in western Spain that feeds into the larger Douro River system.
  • C. Río Funza
    Río Funza is a river in central Colombia that drains the Bogotá savanna and forms the Tequendama Falls before joining the Magdalena River basin.
  • D. Río Daule
    Río Daule is a major river in western Ecuador that flows through the coastal lowlands and plays a key role in the region’s agriculture and settlements.
  • E. Río Lato
    Río Lato is a river in Colombia associated with the municipality of Piedecuesta in the Santander Department.
  • 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d9811add9881908a92186dab5b6d48 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fff78ad38481908df2338aaf276da9 completed May 10, 2026, 3:12 a.m.
Created at: April 9, 2026, 9:01 p.m.