Triple
T15292412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL 208 |
E365559
|
entity |
| Predicate | runningGear |
P85303
|
FINISHED |
| Object | rubber tyres |
—
|
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: rubber tyres | Statement: [VAL 208, runningGear, rubber tyres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runningGear Context triple: [VAL 208, runningGear, rubber tyres]
-
A.
hasRunningGear
chosen
Indicates that an entity is equipped with or possesses running gear, such as the mechanical components that enable movement or operation.
-
B.
runningTerrain
Indicates the type of ground or surface on which the running activity takes place.
-
C.
runningStyle
Indicates the characteristic manner or form in which an entity performs running.
-
D.
runningDiscipline
Indicates a relationship where an entity participates in or is associated with running as a sport or athletic discipline.
-
E.
traditionalFootwear
Indicates that the relationship involves footwear that is characteristic of, or historically associated with, a particular culture, region, or tradition.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.