Triple
T33465848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morocco national under-20 football team |
E857040
|
entity |
| Predicate | africaU20CupOfNationsAppearances |
P176657
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Morocco national under-20 football team, africaU20CupOfNationsAppearances, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: africaU20CupOfNationsAppearances Context triple: [Morocco national under-20 football team, africaU20CupOfNationsAppearances, 6]
-
A.
africaU17CupOfNationsTitles
Indicates the number of Africa U-17 Cup of Nations championship titles an entity has won.
-
B.
africaCupOfNationsAppearances
Indicates the number of times an entity has participated in the Africa Cup of Nations tournament.
-
C.
africaU17Appearances
Indicates the number of times an entity has participated in the Africa U-17 football (soccer) tournament.
-
D.
africaCupOfNationsParticipation
Indicates participation by an entity (typically a team or player) in the Africa Cup of Nations football tournament.
-
E.
africaU17CupOfNationsTitleYear
Indicates the year in which an entity won the Africa U-17 Cup of Nations 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e52a6d40819084472f6072c91e9f |
completed | May 3, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69f6e3da41948190a4cfe866ce184f73 |
completed | May 3, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69f6e47c13348190a10528c84a401178 |
completed | May 3, 2026, 6 a.m. |
Created at: May 1, 2026, 1:37 a.m.