Triple

T33785358
Position Surface form Disambiguated ID Type / Status
Subject Vilcabamba E865770 entity
Predicate locatedOn P40 FINISHED
Object Vilcabamba River
The Vilcabamba River is a waterway in southern Ecuador known for flowing through the Vilcabamba Valley, an area famed for its mild climate and residents’ reputed longevity.
E2149523 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: Vilcabamba River | Statement: [Vilcabamba, locatedOn, Vilcabamba 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: Vilcabamba River
Triple: [Vilcabamba, locatedOn, Vilcabamba River]
Generated description
The Vilcabamba River is a waterway in southern Ecuador known for flowing through the Vilcabamba Valley, an area famed for its mild climate and residents’ reputed longevity.

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_69f3498ecc2c8190bcd85e3f11dc215e completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6fccf8b1081909615ae092ed98361 completed May 3, 2026, 7:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a386829c2fc81909673393043f88bce completed June 21, 2026, 10:39 p.m.
NEDg Description generation batch_6a386913196c81908274a2e909d943b8 completed June 21, 2026, 10:43 p.m.
NED2 Entity disambiguation (via description) batch_6a3869ef06088190a5e72b39204adf85 completed June 21, 2026, 10:47 p.m.
Created at: May 1, 2026, 1:45 a.m.