Triple

T27328465
Position Surface form Disambiguated ID Type / Status
Subject Kunene River E689723 entity
Predicate drainageBasin P1559 FINISHED
Object Kunene River basin
The Kunene River basin is the catchment area in southwestern Africa that collects and channels water from parts of Angola and Namibia into the Kunene River, supporting diverse ecosystems and local communities in an otherwise arid region.
 E1784553 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: Kunene River basin | Statement: [Kunene River, drainageBasin, Kunene River basin]
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: Kunene River basin
Triple: [Kunene River, drainageBasin, Kunene River basin]
Generated description
The Kunene River basin is the catchment area in southwestern Africa that collects and channels water from parts of Angola and Namibia into the Kunene River, supporting diverse ecosystems and local communities in an otherwise arid region.

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_69ef355d4cb08190ab032c0a2e7d3753 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f627ef6bac8190a7edfb950c1ad3c4 completed May 2, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12da6b0288819089e4b2a425670b4b completed May 24, 2026, 11 a.m.
NEDg Description generation batch_6a12ddd102ac8190838e6ee34ebbf295 completed May 24, 2026, 11:15 a.m.
NED2 Entity disambiguation (via description) batch_6a12de788ac081908ee34621742eeef5 completed May 24, 2026, 11:18 a.m.
Created at: April 27, 2026, 11:36 a.m.