Triple

T8611460
Position Surface form Disambiguated ID Type / Status
Subject SD Association E203922 entity
Predicate standardizes P1371 FINISHED
Object SDUC
SDUC is a high-capacity Secure Digital (SD) memory card specification designed to support very large storage sizes and faster data transfer rates for modern devices.
 E745352 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: SDUC | Statement: [SD Association, standardizes, SDUC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SDUC
Context triple: [SD Association, standardizes, SDUC]
  • A. SDU
    SDU is the IATA airport code for Santos Dumont Airport, a major domestic airport serving Rio de Janeiro, Brazil.
  • B. SDC
    SDC is a dust-detecting scientific instrument aboard NASA’s New Horizons spacecraft used to study space dust in the outer solar system.
  • C. DSU
    DSU is the World Trade Organization’s legal framework that sets out the rules and procedures for resolving trade disputes between member countries.
  • D. SCU
    SCU is the IATA airport code for Antonio Maceo International Airport serving Santiago de Cuba, Cuba.
  • E. DUCET
    DUCET is the Default Unicode Collation Element Table, a standard reference used to define the sorting and comparison order of Unicode characters across different languages and scripts.
  • 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: SDUC
Triple: [SD Association, standardizes, SDUC]
Generated description
SDUC is a high-capacity Secure Digital (SD) memory card specification designed to support very large storage sizes and faster data transfer rates for modern devices.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SDUC
Target entity description: SDUC is a high-capacity Secure Digital (SD) memory card specification designed to support very large storage sizes and faster data transfer rates for modern devices.
  • A. SDU
    SDU is the IATA airport code for Santos Dumont Airport, a major domestic airport serving Rio de Janeiro, Brazil.
  • B. SDC
    SDC is a dust-detecting scientific instrument aboard NASA’s New Horizons spacecraft used to study space dust in the outer solar system.
  • C. DSU
    DSU is the World Trade Organization’s legal framework that sets out the rules and procedures for resolving trade disputes between member countries.
  • D. SCU
    SCU is the IATA airport code for Antonio Maceo International Airport serving Santiago de Cuba, Cuba.
  • E. DUCET
    DUCET is the Default Unicode Collation Element Table, a standard reference used to define the sorting and comparison order of Unicode characters across different languages and scripts.
  • 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_69ca832c23e4819095a9f3eea4a21828 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46fc31e08190aab5ab8f92f3315c completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea91456a88190a7416b0f1a0327d6 completed April 2, 2026, 5:36 p.m.
NEDg Description generation batch_69cea9e685388190a4be9d2135dc02d0 completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaababe2c8190bc47430d33bfdbaa completed April 2, 2026, 5:43 p.m.
Created at: March 30, 2026, 6:25 p.m.