Triple
T698625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giro d'Italia |
E13947
|
entity |
| Predicate | jerseySignificance |
P16782
|
FINISHED |
| Object | leader of general classification |
—
|
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: leader of general classification | Statement: [Giro d'Italia, jerseySignificance, leader of general classification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseySignificance Context triple: [Giro d'Italia, jerseySignificance, leader of general classification]
-
A.
jersey
Indicates that one entity is the jersey (sports uniform top) associated with, worn by, or representing another entity.
-
B.
hasRegionalSignificance
Indicates that something holds particular importance, influence, or relevance within a specific geographic region.
-
C.
jerseyNumber
Indicates the specific uniform number assigned to and worn by an individual, typically in a sports context.
-
D.
hasCulturalSignificanceFor
Indicates that something holds particular cultural meaning, value, or importance for a specified group or community.
-
E.
significantMonument
Indicates that something is a monument of notable historical, cultural, or symbolic importance.
- 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_69a493406c408190957eeec9048a8fb6 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a0c99be48190babc37c397b6a186 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d2586b081908e052cc5ba1d2685 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49dc20880819085fa60dc1851f9dc |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:36 p.m.