Triple
T272516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM PC |
E5665
|
entity |
| Predicate | formFactor |
P1464
|
FINISHED |
| Object | desktop |
—
|
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: desktop | Statement: [IBM PC, formFactor, desktop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formFactor Context triple: [IBM PC, formFactor, desktop]
-
A.
platformNeutral
Indicates that something is compatible with, applicable to, or designed to work across multiple platforms without dependence on any specific one.
-
B.
frontType
Indicates the type or category of a front (e.g., boundary or leading side) that one entity presents or forms relative to another.
-
C.
platforms
Indicates that one entity provides or serves as a base, medium, or environment that supports the operation, distribution, or presentation of another entity.
-
D.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
-
E.
shape
chosen
Indicates that one entity has a particular geometric or physical form characterized by the other entity.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dcf667c8190a7b8630fe67b9a90 |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7345c4819086c21710864a1b42 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.