Triple
T9614347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Micron Technology |
E232180
|
entity |
| Predicate | formerSubsidiary |
P6796
|
FINISHED |
| Object |
Lexar
Lexar is a brand known for producing flash memory products such as USB drives, memory cards, and solid-state drives.
|
E812474
|
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: Lexar | Statement: [Micron Technology, formerSubsidiary, Lexar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lexar Context triple: [Micron Technology, formerSubsidiary, 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
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.
Kingston Technology
Kingston Technology is a leading American manufacturer of memory products and storage solutions, including RAM modules, SSDs, and flash drives, for consumer and enterprise markets worldwide.
-
E.
Maxtor Tower
Maxtor Tower is a historic defensive tower that forms part of the medieval fortifications of Nuremberg, Germany.
- 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: Lexar Triple: [Micron Technology, formerSubsidiary, Lexar]
Generated description
Lexar is a brand known for producing flash memory products such as USB drives, memory cards, and solid-state drives.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lexar Target entity description: Lexar is a brand known for producing flash memory products such as USB drives, memory cards, and solid-state drives.
-
A.
LaCie
LaCie is a premium computer storage hardware brand known for its stylish, design-focused external drives and professional storage solutions.
-
B.
SanDisk
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.
Kingston Technology
Kingston Technology is a leading American manufacturer of memory products and storage solutions, including RAM modules, SSDs, and flash drives, for consumer and enterprise markets worldwide.
-
E.
Maxtor Tower
Maxtor Tower is a historic defensive tower that forms part of the medieval fortifications of Nuremberg, Germany.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9aaaa47881908d69381d4d11f49b |
completed | April 1, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18223429c8190b1b96b07155c5742 |
completed | April 4, 2026, 9:26 p.m. |
| NEDg | Description generation | batch_69d1848e065081908be8e23cc9420fcc |
completed | April 4, 2026, 9:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d184f560f4819094e7375f0589c4cd |
completed | April 4, 2026, 9:39 p.m. |
Created at: March 30, 2026, 8:09 p.m.