Triple
T3857949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regency |
E90063
|
entity |
| Predicate | trimType |
P11486
|
FINISHED |
| Object | comfort- and feature-oriented trim level |
—
|
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: comfort- and feature-oriented trim level | Statement: [Regency, trimType, comfort- and feature-oriented trim level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trimType Context triple: [Regency, trimType, comfort- and feature-oriented trim level]
-
A.
trimLevel
chosen
Indicates the specific configuration or package level of features or options applied to an item, typically distinguishing variants within the same base model.
-
B.
rimType
Indicates the specific style or configuration of a rim associated with an object or component.
-
C.
rinkType
Indicates the specific kind or category of rink associated with an entity (e.g., ice rink, roller rink, practice rink).
-
D.
cutFormat
Indicates that one entity trims or shapes another entity into a specified format or pattern.
-
E.
tractionType
Indicates the type or method of traction applied or used in relation to an entity or system.
- 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.