Triple

T13265639
Position Surface form Disambiguated ID Type / Status
Subject Nkangala District Municipality E315915 entity
Predicate hasMunicipalCode P3943 FINISHED
Object DC31
DC31 is the official municipal code assigned to the Nkangala District Municipality in South Africa’s Mpumalanga province.
E1031198 NE FINISHED

How this triple was built (4 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: DC31 | Statement: [Nkangala District Municipality, hasMunicipalCode, DC31]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DC31
Context triple: [Nkangala District Municipality, hasMunicipalCode, DC31]
  • A. DC35
    DC35 is the official municipal code designating the Capricorn District Municipality in South Africa’s Limpopo province.
  • B. DC34
    DC34 is the official municipal code assigned to the Vhembe District Municipality in South Africa.
  • C. DC37
    DC37 is the official district code designating the Bojanala Platinum District in South Africa’s North West province.
  • D. DC3
    DC3 is a public community college in Dodge City, Kansas, offering two-year academic and technical programs.
  • E. DC39
    DC39 is the official administrative district code assigned to the Dr Ruth Segomotsi Mompati District in South Africa’s North West Province.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: DC31
Triple: [Nkangala District Municipality, hasMunicipalCode, DC31]
Generated description
DC31 is the official municipal code assigned to the Nkangala District Municipality in South Africa’s Mpumalanga province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DC31
Target entity description: DC31 is the official municipal code assigned to the Nkangala District Municipality in South Africa’s Mpumalanga province.
  • A. DC35
    DC35 is the official municipal code designating the Capricorn District Municipality in South Africa’s Limpopo province.
  • B. DC34
    DC34 is the official municipal code assigned to the Vhembe District Municipality in South Africa.
  • C. DC37
    DC37 is the official district code designating the Bojanala Platinum District in South Africa’s North West province.
  • D. DC3
    DC3 is a public community college in Dodge City, Kansas, offering two-year academic and technical programs.
  • E. DC39
    DC39 is the official administrative district code assigned to the Dr Ruth Segomotsi Mompati District in South Africa’s North West Province.
  • F. None of above. chosen

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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901e44bc8190966f87ae219d6bf4 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a4ad79c8190b1304942dc48c0ff completed May 3, 2026, 8:41 a.m.
NEDg Description generation batch_69f70b37ebe081909ed2ae0f42ccad2d completed May 3, 2026, 8:45 a.m.
NED2 Entity disambiguation (via description) batch_69f70ca343f08190b6484f464ed40810 completed May 3, 2026, 8:51 a.m.
Created at: April 9, 2026, 9:25 p.m.