Triple
T618944
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuelta a España |
E14467
|
entity |
| Predicate | jerseyColorMountainsClassification |
P16708
|
FINISHED |
| Object | polka‑dot jersey |
—
|
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: polka‑dot jersey | Statement: [Vuelta a España, jerseyColorMountainsClassification, polka‑dot jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyColorMountainsClassification Context triple: [Vuelta a España, jerseyColorMountainsClassification, polka‑dot jersey]
-
A.
jersey
Indicates that one entity is the jersey (sports uniform top) associated with, worn by, or representing another entity.
-
B.
jerseySecondaryColor
Indicates the secondary or accent color used on an entity’s jersey.
-
C.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
D.
hillColor
Indicates the color attribute associated with a hill.
-
E.
hasMountain
Indicates that a location or region possesses or contains at least one mountain.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfd15288190b4abdbd0bce3edcd |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49d76062c819083ac33f1f87097c7 |
completed | March 1, 2026, 8:11 p.m. |
Created at: March 1, 2026, 7:35 p.m.