Triple

T23647277
Position Surface form Disambiguated ID Type / Status
Subject Vhembe region E584071 entity
Predicate contains P35 FINISHED
Object Soutpansberg mountain range
The Soutpansberg mountain range is a biodiverse and geologically ancient mountain chain in northern Limpopo, South Africa, known for its rich endemic flora and fauna and cultural significance.
E1644474 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: Soutpansberg mountain range | Statement: [Vhembe region, contains, Soutpansberg mountain range]
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: Soutpansberg mountain range
Triple: [Vhembe region, contains, Soutpansberg mountain range]
Generated description
The Soutpansberg mountain range is a biodiverse and geologically ancient mountain chain in northern Limpopo, South Africa, known for its rich endemic flora and fauna and cultural significance.

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_69e248fefafc81909656921192f30e80 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b28643348190add3666638951680 completed April 29, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10044b44108190b3a6a9bc1bdf41ae completed May 22, 2026, 7:22 a.m.
NEDg Description generation batch_6a100710ac5081908fe0e6c9ff7a2273 completed May 22, 2026, 7:34 a.m.
NED2 Entity disambiguation (via description) batch_6a1007a4b0a08190ad91e9c327c2ff65 completed May 22, 2026, 7:37 a.m.
Created at: April 17, 2026, 6:48 p.m.