Triple
T8611487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SD Association |
E203922
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Lexar |
E45907
|
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: Lexar | Statement: [SD Association, hasMember, Lexar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lexar Context triple: [SD Association, hasMember, Lexar]
-
A.
LaCie
LaCie is a premium computer storage hardware brand known for its stylish, design-focused external drives and professional storage solutions.
-
B.
SanDisk
chosen
SanDisk is a prominent data storage brand known for its flash memory products such as SD cards, USB drives, and solid-state drives.
-
C.
Iomega
Iomega was a data storage company best known for its Zip and Jaz drives, later acquired and operated as a subsidiary of EMC Corporation.
-
D.
Maxtor Tower
Maxtor Tower is a historic defensive tower that forms part of the medieval fortifications of Nuremberg, Germany.
-
E.
Western Digital
Western Digital is a major American data storage company known for manufacturing hard disk drives, solid-state drives, and related storage solutions for consumers and enterprises.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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. |
Created at: March 30, 2026, 6:25 p.m.