Triple
T24976704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raleigh Twenty |
E625040
|
entity |
| Predicate | hasMudguards |
P159709
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Raleigh Twenty, hasMudguards, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMudguards Context triple: [Raleigh Twenty, hasMudguards, true]
-
A.
hasRim
Indicates that one entity possesses or is equipped with a rim as a defining part or feature.
-
B.
hasHandlebarFairing
Indicates that an object is equipped with a fairing specifically mounted on or integrated into its handlebars.
-
C.
isRubberTyred
Indicates that something operates or is equipped with rubber tires rather than steel wheels or another type of running gear.
-
D.
hasArrestingGear
Indicates that an entity is equipped with a system or mechanism used to rapidly decelerate and stop another entity, typically during landing or capture.
-
E.
hasGuardBars
Indicates that one entity is equipped with or protected by guard bars installed on or around it.
- 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_69e2ff254570819093d197b1900305ac |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f5f7a205688190b8f36bff5013247c |
completed | May 2, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f5afd5baac8190bb8ed576813c8591 |
completed | May 2, 2026, 8:03 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 18, 2026, 6:02 a.m.