Triple
T36075651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | De Dion rear axle |
E1043488
|
entity |
| Predicate | mountsDifferential |
P2519
|
FINISHED |
| Object | to vehicle body |
—
|
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: to vehicle body | Statement: [De Dion rear axle, mountsDifferential, to vehicle body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mountsDifferential Context triple: [De Dion rear axle, mountsDifferential, to vehicle body]
-
A.
hasDifferential
Indicates that one entity is the derivative or rate-of-change expression corresponding to another entity.
-
B.
isDifferential
Indicates that one quantity represents the infinitesimal change or derivative of another with respect to a given variable.
-
C.
differentials
Indicates that there are measurable differences or distinctions between two or more related quantities, states, or conditions.
-
D.
mountType
chosen
Indicates the manner or configuration in which one object is mounted or attached to another.
-
E.
runDifferential
Indicates performing a comparative analysis between two versions, states, or datasets to identify and process their differences.
- 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_69f76e2fd3248190b900d9a492bf5a7a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:08 p.m.