Triple
T27702072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federale 102 |
E698452
|
entity |
| Predicate | usedInTypeOfMatches |
P107100
|
FINISHED |
| Object | international football matches |
—
|
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: international football matches | Statement: [Federale 102, usedInTypeOfMatches, international football matches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInTypeOfMatches Context triple: [Federale 102, usedInTypeOfMatches, international football matches]
-
A.
usedInMatchType
chosen
Indicates that something (such as a rule, item, or configuration) is applied or relevant within a specific type or category of match.
-
B.
usedInMatch
Indicates that something (such as an item, tactic, or resource) was employed or utilized during a particular match or game.
-
C.
usedInType
Indicates that something serves as a component, element, or example within a particular type or category.
-
D.
usesMatchType
Indicates that one entity applies or operates according to a specific type or category of matching criteria defined by another entity.
-
E.
hasTypeOfMatches
Indicates that one entity has matches that are of a specified type or category in relation to 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_69ef590ea74081908f0cd7500d85fa27 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 27, 2026, 2:57 p.m.