Triple

T35287761
Position Surface form Disambiguated ID Type / Status
Subject Dawid Kruiper Local Municipality E1019134 entity
Predicate borderedBy P224 FINISHED
Object Kgatelopele Local Municipality
Kgatelopele Local Municipality is a rural local municipality in South Africa’s Northern Cape province, known for its sparse population, mining activities, and semi-arid landscape.
E2288920 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: Kgatelopele Local Municipality | Statement: [Dawid Kruiper Local Municipality, borderedBy, Kgatelopele Local Municipality]
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: Kgatelopele Local Municipality
Triple: [Dawid Kruiper Local Municipality, borderedBy, Kgatelopele Local Municipality]
Generated description
Kgatelopele Local Municipality is a rural local municipality in South Africa’s Northern Cape province, known for its sparse population, mining activities, and semi-arid landscape.

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_69f76de6d39c8190bb11342e4b91ff2b completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78fe35fd88190b2154c89e1b7ffd8 completed May 3, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5aeb3de150819092f69d6e38ab35c6 completed July 18, 2026, 2:55 a.m.
NEDg Description generation batch_6a5aec0c5e1c81908837552d7332bcf9 completed July 18, 2026, 2:59 a.m.
NED2 Entity disambiguation (via description) batch_6a5aec63e92481909e371c46c4c19809 completed July 18, 2026, 3 a.m.
Created at: May 3, 2026, 4:03 p.m.