Triple
T22963632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egypt women's national football team |
E570973
|
entity |
| Predicate | africaWomenCupOfNationsAppearances |
P150416
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Egypt women's national football team, africaWomenCupOfNationsAppearances, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: africaWomenCupOfNationsAppearances Context triple: [Egypt women's national football team, africaWomenCupOfNationsAppearances, 2]
-
A.
africaCupOfNationsAppearances
Indicates the number of times an entity has participated in the Africa Cup of Nations tournament.
-
B.
africaCupOfNationsParticipation
Indicates participation by an entity (typically a team or player) in the Africa Cup of Nations football tournament.
-
C.
AfricaCupOfNationsRunnersUp
Indicates that the subject finished as the runner-up (second place) in an edition of the Africa Cup of Nations tournament.
-
D.
wonAfricaCupOfNations
Indicates that the subject has won the Africa Cup of Nations football tournament.
-
E.
africaCupOfNationsBestResult
Indicates the best performance or highest achievement a team or participant has attained in the Africa Cup of Nations tournament.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f66fbc8190a4a7b73d17537132 |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:47 p.m.