Triple
T24454700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portugal national futsal team |
E616648
|
entity |
| Predicate | futsalFinalissimaTitles |
P156172
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Portugal national futsal team, futsalFinalissimaTitles, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: futsalFinalissimaTitles Context triple: [Portugal national futsal team, futsalFinalissimaTitles, 1]
-
A.
FIFAFutsalWorldCupTitles
Indicates the number of FIFA Futsal World Cup championship titles an entity has won.
-
B.
FIFAFutsalWorldCupTitleYear
Indicates the specific year in which a given entity won the FIFA Futsal World Cup title.
-
C.
UEFAInterCitiesFairsCupTitles
Indicates the number of UEFA Inter-Cities Fairs Cup titles an entity has won.
-
D.
FACupTitles
Indicates the number of FA Cup titles that an entity (typically a football club) has won.
-
E.
FIFAConfederationsCupTitleYear
Indicates the specific year in which an entity won a FIFA Confederations Cup title.
- 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_69e2d7ef9fe08190a0613908758b4e86 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f298c4f1d881909d9119fec74afe53 |
completed | April 29, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:18 a.m.