Triple
T11520720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power Macintosh G4 (AGP Graphics) |
E273153
|
entity |
| Predicate | frontSideBus |
P99927
|
FINISHED |
| Object | 100 MHz |
—
|
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: 100 MHz | Statement: [Power Macintosh G4 (AGP Graphics), frontSideBus, 100 MHz]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontSideBus Context triple: [Power Macintosh G4 (AGP Graphics), frontSideBus, 100 MHz]
-
A.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
B.
frontSector
Indicates that one entity is located in the forward-facing sector or region relative to another entity.
-
C.
frontOf
Indicates that one entity is positioned directly before another along a primary viewing or movement direction.
-
D.
partOfFront
Indicates that one entity constitutes a component or section located at the front portion of another entity.
-
E.
frontSightType
Indicates the specific kind or design of the front sight used on an object, typically a firearm or similar aiming device.
- 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_69d6aae2c3748190bed2ea50dfb160dc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd129c88190893b95222480e04a |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80876e5f0819088cff2e72f773cf6 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d822ef46988190a1c360da4ee14fef |
completed | April 9, 2026, 10:06 p.m. |
Created at: April 8, 2026, 9:36 p.m.