Triple

T5794547
Position Surface form Disambiguated ID Type / Status
Subject Supreme Court of Appeal of South Africa E128474 entity
Predicate abbreviation P43 FINISHED
Object SCA
The SCA is South Africa’s highest court of appeal for non-constitutional matters, based in Bloemfontein.
 E546543 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: SCA | Statement: [Supreme Court of Appeal of South Africa, abbreviation, SCA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SCA
Context triple: [Supreme Court of Appeal of South Africa, abbreviation, SCA]
  • A. SCA
    SCA is a U.S. federal law that governs the privacy and disclosure of stored electronic communications and related data held by service providers.
  • B. SCA
    SCA is the National Rail station code for Scarborough railway station in North Yorkshire, England.
  • C. SCA
    SCA is a software composition analysis solution that identifies and manages vulnerabilities and license risks in open-source components used within applications.
  • D. SCHA
    SCHA is the stock ticker symbol under which Schibsted, a Nordic media and online marketplace company, is traded on financial markets.
  • E. SCAR
    SCAR is an international scientific body that coordinates and promotes research in and about Antarctica and the Southern Ocean.
  • 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: SCA
Triple: [Supreme Court of Appeal of South Africa, abbreviation, SCA]
Generated description
The SCA is South Africa’s highest court of appeal for non-constitutional matters, based in Bloemfontein.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SCA
Target entity description: The SCA is South Africa’s highest court of appeal for non-constitutional matters, based in Bloemfontein.
  • A. SCA
    SCA is the National Rail station code for Scarborough railway station in North Yorkshire, England.
  • B. SCA
    SCA is a U.S. federal law that governs the privacy and disclosure of stored electronic communications and related data held by service providers.
  • C. SCA
    SCA is a software composition analysis solution that identifies and manages vulnerabilities and license risks in open-source components used within applications.
  • D. SCHA
    SCHA is the stock ticker symbol under which Schibsted, a Nordic media and online marketplace company, is traded on financial markets.
  • E. SCAR
    SCAR is an international scientific body that coordinates and promotes research in and about Antarctica and the Southern Ocean.
  • 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_69c00845ca68819081a2ce3ecca577f7 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02a91c7788190936671bf816d3772 completed March 22, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c098286c1c8190b77cbaeda327dba4 completed March 23, 2026, 1:32 a.m.
NEDg Description generation batch_69c098a0325c81909a1326b94e40ed50 completed March 23, 2026, 1:34 a.m.
NED2 Entity disambiguation (via description) batch_69c09943deec819085992c4e44050a34 completed March 23, 2026, 1:37 a.m.
Created at: March 22, 2026, 3:51 p.m.