Triple
T6008949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Group C (UEFA Euro 2020) |
E133782
|
entity |
| Predicate | totalTeamsQualifyingFromGroup |
P68719
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Group C (UEFA Euro 2020), totalTeamsQualifyingFromGroup, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalTeamsQualifyingFromGroup Context triple: [Group C (UEFA Euro 2020), totalTeamsQualifyingFromGroup, 3]
-
A.
numberOfQualifiedTeamsFromAsiaOceania
Indicates the count of teams from the Asia-Oceania region that meet the specified qualification criteria.
-
B.
numberOfQualifiedTeamsFromAfrica
Indicates the count of teams from Africa that meet the specified qualification criteria.
-
C.
numberOfQualifiedTeamsFromSouthAmerica
Indicates the count of teams from South America that meet the specified qualification criteria.
-
D.
numberOfQualifiedTeamsFromCONCACAF
Indicates the count of teams from the CONCACAF region that have successfully qualified for a particular competition or tournament.
-
E.
numberOfQualifiedTeamsFromEurope
Indicates the count of teams from Europe that meet the specified qualification criteria.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f4e27a881909cc3f7fef62abc3b |
completed | March 22, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:06 p.m.