Triple

T24592524
Position Surface form Disambiguated ID Type / Status
Subject O'Higgins Lake E608573 entity
Predicate outflow P967 FINISHED
Object Río Pascua
Río Pascua is a remote, fast-flowing river in Chilean Patagonia known for draining the Southern Patagonian Ice Field via O'Higgins Lake into the Pacific Ocean and for its largely untouched natural surroundings.
 E1756053 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 Pascua | Statement: [O'Higgins Lake, outflow, Río Pascua]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Río Pascua
Triple: [O'Higgins Lake, outflow, Río Pascua]
Generated description
Río Pascua is a remote, fast-flowing river in Chilean Patagonia known for draining the Southern Patagonian Ice Field via O'Higgins Lake into the Pacific Ocean and for its largely untouched natural surroundings.

Provenance (5 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_69e2c4cf54248190af7b0c2d9ade9830 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a9dc63208190b70f57b9821a7241 completed April 30, 2026, 1:01 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1247c94bc48190af7b969991842c60 completed May 24, 2026, 12:35 a.m.
NEDg Description generation batch_6a12488822208190aab1355ac3efd2a6 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124935c01c8190b9d6d13c4f50a104 completed May 24, 2026, 12:41 a.m.
Created at: April 18, 2026, 2:30 a.m.