Triple
T5871877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Ahly SC |
E130534
|
entity |
| Predicate | homeCountryLeagueTitlesRecord |
P63945
|
FINISHED |
| Object | record number of Egyptian Premier League titles |
—
|
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: record number of Egyptian Premier League titles | Statement: [Al Ahly SC, homeCountryLeagueTitlesRecord, record number of Egyptian Premier League titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: homeCountryLeagueTitlesRecord Context triple: [Al Ahly SC, homeCountryLeagueTitlesRecord, record number of Egyptian Premier League titles]
-
A.
numberOfLeagueTitles
chosen
Indicates the total count of league championship titles that an entity has won.
-
B.
nationalTeamTitles
Indicates the number of titles or championships an entity has won while representing its national team.
-
C.
nationalTeamTitleCount
Indicates the number of titles or championships a national team has won.
-
D.
team1LeagueTitles
Indicates the number of league titles that the first team has won.
-
E.
uefaNationsLeagueTitles
Indicates the number of UEFA Nations League championship titles an entity (typically a national football team) has won.
- 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_69c0085047dc8190af24e311edad3c07 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0432fea5881909f5c291dd8db6105 |
completed | March 22, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69c033499ca08190bd26cee5b03f6306 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:56 p.m.