Triple
T315510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Wayne Assembly |
E7696
|
entity |
| Predicate | hasBodyStyleFocus |
P8243
|
FINISHED |
| Object | pickup truck |
—
|
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: pickup truck | Statement: [Fort Wayne Assembly, hasBodyStyleFocus, pickup truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyStyleFocus Context triple: [Fort Wayne Assembly, hasBodyStyleFocus, pickup truck]
-
A.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
B.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
C.
primaryBodyStyle
chosen
Indicates the main or predominant body configuration or structural form associated with an entity.
-
D.
hasCollectionFocus
Indicates that something is primarily concerned with, centered on, or directed toward a particular collection or set of items.
-
E.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea6462148190825acc57f6d2adaf |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e943f12c8190883854aeed974260 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.