Triple
T38209896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1. FFC Frankfurt |
E1010509
|
entity |
| Predicate | UEFAWomen'sTitles |
P190289
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [1. FFC Frankfurt, UEFAWomen'sTitles, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UEFAWomen'sTitles Context triple: [1. FFC Frankfurt, UEFAWomen'sTitles, 4]
-
A.
UEFAWomensCupTitleSeason
Indicates the specific season in which a team won the UEFA Women's Cup title.
-
B.
bestUefaWomen’sChampionshipResult
Indicates the highest level of success an entity has achieved in the UEFA Women's Championship competition.
-
C.
uefaNationsLeagueTitles
Indicates the number of UEFA Nations League championship titles an entity (typically a national football team) has won.
-
D.
EuropeanChampionshipTitles
Indicates the number of European Championship titles an entity has won.
-
E.
UEFAInterCitiesFairsCupTitles
Indicates the number of UEFA Inter-Cities Fairs Cup titles an entity has won.
- 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcc42cbac48190b8d3e4c9ce140838 |
completed | May 7, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69fcb0fc69c88190800453eb57a7e62c |
completed | May 7, 2026, 3:34 p.m. |
| PDg | Predicate description generation | batch_69fcc42b9334819099929649b7ef68ea |
completed | May 7, 2026, 4:56 p.m. |
Created at: May 3, 2026, 4:30 p.m.