Triple

T33171900
Position Surface form Disambiguated ID Type / Status
Subject Aluminé Lake E849055 entity
Predicate inflow P415 FINISHED
Object Aluminé River
The Aluminé River is a Patagonian river in Argentina that flows through the Neuquén Province, known for its scenic Andean landscapes and popularity for fishing and whitewater rafting.
 E2297562 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: Aluminé River | Statement: [Aluminé Lake, inflow, Aluminé River]
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: Aluminé River
Triple: [Aluminé Lake, inflow, Aluminé River]
Generated description
The Aluminé River is a Patagonian river in Argentina that flows through the Neuquén Province, known for its scenic Andean landscapes and popularity for fishing and whitewater rafting.

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_69f3495be8808190bbf427733df08aad completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d956408481908e95e80cbd9908d3 completed May 3, 2026, 5:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a83a627ec88819094a5028a821a741b completed Aug. 18, 2026, 12:24 a.m.
NEDg Description generation batch_6a83a67723ac8190b04b6b846f9bee8f completed Aug. 18, 2026, 12:25 a.m.
NED2 Entity disambiguation (via description) batch_6a83a705a05c8190a1505ffade5ec704 completed Aug. 18, 2026, 12:27 a.m.
Created at: May 1, 2026, 1:29 a.m.