Triple
T30338912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | POWER10 |
E771694
|
entity |
| Predicate | processTechnologyProvider |
P160830
|
FINISHED |
| Object | Samsung 7 nm EUV |
—
|
LITERAL 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: Samsung 7 nm EUV | Statement: [POWER10, processTechnologyProvider, Samsung 7 nm EUV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processTechnologyProvider Context triple: [POWER10, processTechnologyProvider, Samsung 7 nm EUV]
-
A.
laterTechnologySupplier
Indicates that one entity supplies technology to another at a later time or in a subsequent stage relative to some reference point or sequence.
-
B.
serviceTechnology
Indicates that a particular technology is used to implement, support, or deliver a given service.
-
C.
enablesTechnology
Indicates that one entity makes it possible for another entity, system, or process to function through the use or provision of a particular technology.
-
D.
appliesTechnologyIn
chosen
Indicates that an entity makes use of or implements a particular technology within a specific context or activity.
-
E.
mainGenerationTechnology
Indicates the primary technology or method used to generate something, typically identifying the dominant production or generation approach among possible alternatives.
- F. None of above.
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_69f2248aba24819095bb86480d55b23b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f681cf69588190b1a6373ddf29dd6a |
completed | May 2, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:55 p.m.