Triple
T23169594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | black No. 3 Goodwrench Chevrolet |
E578807
|
entity |
| Predicate | numberStyle |
P3378
|
FINISHED |
| Object | white No. 3 with red outline |
—
|
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: white No. 3 with red outline | Statement: [black No. 3 Goodwrench Chevrolet, numberStyle, white No. 3 with red outline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberStyle Context triple: [black No. 3 Goodwrench Chevrolet, numberStyle, white No. 3 with red outline]
-
A.
usesNumeralsFrom
Indicates that one writing system, notation, or representation employs the numeral symbols originating from another system.
-
B.
hasNumberDistinction
Indicates that a language or system grammatically distinguishes between different numbers (such as singular, plural, dual, etc.) in its expressions.
-
C.
numberingSystemBasedOn
Indicates that one numbering system is derived from, structured according to, or conceptually dependent on another numbering system.
-
D.
numberingType
chosen
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
E.
notationSystem
Indicates a relationship where one entity is the system or method of notation used to represent or encode another entity.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2f10208190b3a0f9a4c790cb0a |
completed | April 29, 2026, 4:55 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:03 p.m.