Triple
T35167210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Classico français |
E1015435
|
entity |
| Predicate | importanceInLeague |
P182903
|
FINISHED |
| Object | marquee fixture |
—
|
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: marquee fixture | Statement: [Le Classico français, importanceInLeague, marquee fixture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: importanceInLeague Context triple: [Le Classico français, importanceInLeague, marquee fixture]
-
A.
importanceWithinSport
Indicates the degree to which something is regarded as significant or influential within a particular sport.
-
B.
importanceInSeason
Indicates the degree to which something is significant or influential within a specific season or seasonal context.
-
C.
hasRegularSeasonImportance
Indicates that something possesses significance or relevance specifically within the context of a regular season.
-
D.
importanceInRacing
Indicates the degree to which something plays a significant or influential role within the context of racing.
-
E.
importanceInLap
Indicates the degree to which something is significant or influential within a specific lap or iteration of an event or process.
- 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_69f76ddbfde081908bffc91572368289 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f794f24e588190965e39b77534d53f |
completed | May 3, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
| PDg | Predicate description generation | batch_69f791cad5e08190a8a04ca283dbecaa |
completed | May 3, 2026, 6:19 p.m. |
Created at: May 3, 2026, 4:02 p.m.