Triple
T1832301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | exFAT |
E40785
|
entity |
| Predicate | standardizedBy |
P1371
|
FINISHED |
| Object |
SD Association
The SD Association is an industry consortium that develops and maintains standards for Secure Digital (SD) memory cards and related technologies.
|
E203922
|
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: SD Association | Statement: [exFAT, standardizedBy, SD Association]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SD Association Context triple: [exFAT, standardizedBy, SD Association]
-
A.
SES
SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
-
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.
AMS
AMS is the three-letter IATA airport code for Amsterdam Airport Schiphol, the main international airport of the Netherlands.
-
D.
AMS
AMS is a United States Department of Agriculture agency that develops quality standards, grading, and marketing programs for agricultural products to support fair and efficient markets.
-
E.
SAN
SAN is the three-letter IATA airport code for San Diego International Airport, the primary commercial airport serving the San Diego, California area.
- 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: SD Association Triple: [exFAT, standardizedBy, SD Association]
Generated description
The SD Association is an industry consortium that develops and maintains standards for Secure Digital (SD) memory cards and related technologies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SD Association Target entity description: The SD Association is an industry consortium that develops and maintains standards for Secure Digital (SD) memory cards and related technologies.
-
A.
SES
SES is the commonly used abbreviation for St Edward's School, a co-educational independent boarding and day school in Oxford, England.
-
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.
AMS
AMS is the three-letter IATA airport code for Amsterdam Airport Schiphol, the main international airport of the Netherlands.
-
D.
AMS
AMS is a United States Department of Agriculture agency that develops quality standards, grading, and marketing programs for agricultural products to support fair and efficient markets.
-
E.
SAN
SAN is the three-letter IATA airport code for San Diego International Airport, the primary commercial airport serving the San Diego, California area.
- 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_69a8864644bc8190b2358ab897194ac1 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb024287c8190b68aa070e556a381 |
completed | March 7, 2026, 4:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf6f212c8190b0d182f8486d9e47 |
completed | March 8, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69adc080abb88190883c35943dc7cb10 |
completed | March 8, 2026, 6:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adc13330888190a2b99c6fcbb97d49 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 4, 2026, 7:32 p.m.