Triple

T24740052
Position Surface form Disambiguated ID Type / Status
Subject Runde River E618528 entity
Predicate alsoKnownAs P39 FINISHED
Object Lundi River
The Lundi River, more commonly known as the Runde River, is a major river in southeastern Zimbabwe that flows through the Gonarezhou National Park before joining the Save River.
 E2291729 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: Lundi River | Statement: [Runde River, alsoKnownAs, Lundi 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: Lundi River
Triple: [Runde River, alsoKnownAs, Lundi River]
Generated description
The Lundi River, more commonly known as the Runde River, is a major river in southeastern Zimbabwe that flows through the Gonarezhou National Park before joining the Save River.

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_69e2fab8f95c81908bb9e552cf3280c2 completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f41055c0e48190b610145ed88c002b completed May 1, 2026, 2:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c846c62bc819090258464e6ec5bc4 completed July 19, 2026, 8:01 a.m.
NEDg Description generation batch_6a5c85216f848190a905a237a95083e9 completed July 19, 2026, 8:04 a.m.
NED2 Entity disambiguation (via description) batch_6a5c85713e708190be341dbdd21a7897 completed July 19, 2026, 8:06 a.m.
Created at: April 18, 2026, 4:04 a.m.