Triple
T15836043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chrysler Financial |
E383985
|
entity |
| Predicate | financedAssetType |
P15055
|
FINISHED |
| Object | new vehicles |
—
|
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: new vehicles | Statement: [Chrysler Financial, financedAssetType, new vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: financedAssetType Context triple: [Chrysler Financial, financedAssetType, new vehicles]
-
A.
assetType
chosen
Indicates the specific category or classification of an asset within a broader asset framework or system.
-
B.
loanType
Indicates the specific category or kind of loan associated with an entity or transaction.
-
C.
collateralType
Indicates the kind or category of collateral associated with an obligation, agreement, or financial exposure.
-
D.
lenderType
Indicates the classification or category of the lender involved in a lending relationship (e.g., bank, individual, institution).
-
E.
finType
Indicates that an entity is of a finite type, meaning it has only a finite number of distinct possible values or elements.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e0e1cc8190851b30b03cf9c9b8 |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:49 a.m.