Triple
T35179019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2021 Africa Cup of Nations |
E1015793
|
entity |
| Predicate | bestGoalkeeperTeam |
P182362
|
FINISHED |
| Object | Senegal national football team |
—
|
NE NERFINISHED |
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: Senegal national football team | Statement: [2021 Africa Cup of Nations, bestGoalkeeperTeam, Senegal national football team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestGoalkeeperTeam Context triple: [2021 Africa Cup of Nations, bestGoalkeeperTeam, Senegal national football team]
-
A.
bestGoalkeeper
Indicates that the subject is considered the top-performing or most skilled goalkeeper among a specified group or context.
-
B.
mostWinsGoaltenderTeam
Indicates that a team is the one for which a given goaltender has recorded the highest number of wins.
-
C.
topScorerTeam
Indicates that a given team is the one with the highest score (or total points) in a particular game, season, or competition.
-
D.
mostAwardsHolderTeam
Indicates the team that holds the highest number of awards within a given set or competition.
-
E.
goalScorerTeam
Indicates that a team is the one for which a particular goal scorer scored a goal.
- 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d78d7c8819081e37e0881eafd91 |
completed | May 3, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.