Triple
T34294464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Mustang Bullitt (Coyote-based) |
E879983
|
entity |
| Predicate | hasDesignCue |
P198928
|
FINISHED |
| Object | minimal exterior badging |
—
|
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: minimal exterior badging | Statement: [Ford Mustang Bullitt (Coyote-based), hasDesignCue, minimal exterior badging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDesignCue Context triple: [Ford Mustang Bullitt (Coyote-based), hasDesignCue, minimal exterior badging]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
hasDesignSide
Indicates that one entity is located on, associated with, or corresponds to a particular side or face of another entity’s design.
-
C.
hasDesignConsideration
Indicates that one entity takes another entity into account as a factor, constraint, or requirement in its design or planning.
-
D.
hasDesignIntent
Indicates that one entity embodies or reflects the planned purpose, function, or conceptual intent defined by another entity.
-
E.
hasDesignSignificance
Indicates that something possesses notable importance, impact, or relevance specifically in terms of its design.
- F. None of above. chosen
Provenance (4 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
| PDg | Predicate description generation | batch_69ff14d4dfc48190bc9fba2384988a98 |
completed | May 9, 2026, 11:04 a.m. |
Created at: May 1, 2026, 1:57 a.m.