Triple
T3857934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regency |
E90063
|
entity |
| Predicate | appliedToBodyStyle |
P23419
|
FINISHED |
| Object | full-size sedan |
—
|
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: full-size sedan | Statement: [Regency, appliedToBodyStyle, full-size sedan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToBodyStyle Context triple: [Regency, appliedToBodyStyle, full-size sedan]
-
A.
appliedToBody
Indicates that something (such as a substance, treatment, or device) is put onto or used directly on a body or body part.
-
B.
associatedWithBodyStyles
chosen
Indicates a relationship where something (such as a product, model, or item) is linked or connected to one or more specific body styles.
-
C.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
D.
belongsToBody
Indicates that something is a part of, or under the ownership/authority of, a particular body or organization.
-
E.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1e68f88190941c39221486f6ae |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.