Triple
T27581952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Model F keyboard systems |
E699605
|
entity |
| Predicate | tactileProfile |
P47694
|
FINISHED |
| Object | sharp tactile bump |
—
|
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: sharp tactile bump | Statement: [IBM Model F keyboard systems, tactileProfile, sharp tactile bump]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tactileProfile Context triple: [IBM Model F keyboard systems, tactileProfile, sharp tactile bump]
-
A.
hasRidges
Indicates that one entity possesses raised, linear or patterned ridges on its surface or structure in relation to another entity or context.
-
B.
stemTexture
Indicates the surface quality or feel of a stem, such as whether it is smooth, rough, hairy, or otherwise textured.
-
C.
hasTactileStripsOnPlatformEdges
Indicates that tactile strips are present along the edges of a platform to provide a detectable boundary or warning surface.
-
D.
palateProfile
Indicates the characteristic taste and flavor qualities associated with something, such as a food or beverage.
-
E.
surfaceFeatureOf
chosen
Indicates that one entity is a surface-level characteristic, pattern, or feature belonging to or present on another 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 2:03 p.m.