Triple
T17537411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tensor G3 |
E427096
|
entity |
| Predicate | mediumCoreCount |
P127833
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Tensor G3, mediumCoreCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mediumCoreCount Context triple: [Tensor G3, mediumCoreCount, 4]
-
A.
mediumIncludes
Indicates that a given medium contains, encompasses, or incorporates another item, component, or element within it.
-
B.
medium
Indicates that an entity serves as the means, channel, or intermediary through which an action, communication, or effect is carried out between other entities.
-
C.
mediumDisplayed
Indicates that a particular medium (such as an image, video, or document) is being shown or rendered in a given context or interface.
-
D.
mediumCategory
Indicates the classification of an item or content according to the type or form of medium it belongs to (e.g., print, digital, audio, video).
-
E.
bigCoreCount
Indicates that an entity (such as a processor or system) has a relatively large number of cores compared to a typical or baseline configuration.
- 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4536d03dc81908b8a58f66657c01a |
completed | April 19, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f8b9888190aa8a45e09acf4319 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:49 a.m.