Triple
T27749870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Lake-Y |
E702087
|
entity |
| Predicate | dieSizeCategory |
P62521
|
FINISHED |
| Object | small mobile SoC |
—
|
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: small mobile SoC | Statement: [Amber Lake-Y, dieSizeCategory, small mobile SoC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dieSizeCategory Context triple: [Amber Lake-Y, dieSizeCategory, small mobile SoC]
-
A.
dieSize
Indicates the size or number of faces of a die used in a game or randomization context.
-
B.
discSize
Indicates the size or capacity of a disc in the relationship or context being described.
-
C.
sizeCategory
chosen
Indicates the relative size classification assigned to an entity compared to others (e.g., small, medium, large).
-
D.
weightSize
Indicates a relationship between an entity’s weight and its physical size, typically expressing how one varies or is characterized in terms of the other.
-
E.
sizeType
Indicates the kind or category of size associated with an entity, such as relative scale, measurement type, or size classification.
- 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_69ef6a53c7388190899baa6daf42301c |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6371e33808190bd66d358dbd8d725 |
completed | May 2, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69f63188e7408190af8ce8b93d128c63 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 4:19 p.m.