Triple
T27885109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaby Lake Refresh |
E705203
|
entity |
| Predicate | notebookSegment |
P163253
|
FINISHED |
| Object | ultrabook |
—
|
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: ultrabook | Statement: [Kaby Lake Refresh, notebookSegment, ultrabook]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notebookSegment Context triple: [Kaby Lake Refresh, notebookSegment, ultrabook]
-
A.
notabilityScope
Indicates the domain, field, or context within which something is considered notable or significant.
-
B.
designerNotability
Indicates that an entity is notable or recognized specifically for its work or role as a designer.
-
C.
notableSect
Indicates that an entity is a significant or prominent sect, denomination, or subgroup within a broader religious, ideological, or organizational context.
-
D.
notabilityStatus
Indicates whether and how an entity is recognized as notable or significant within a given context or system.
-
E.
notableSection
Indicates that a particular part or segment of something is especially important, prominent, or worthy of attention within the whole.
- F. None of above. chosen
Provenance (4 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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f639b09d208190a78de29906514a12 |
completed | May 2, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69f6318be69481909d1bcf29b7b60eb2 |
completed | May 2, 2026, 5:17 p.m. |
| PDg | Predicate description generation | batch_69f6352df6148190bc10772cd40bd7b3 |
completed | May 2, 2026, 5:32 p.m. |
Created at: April 27, 2026, 6:32 p.m.