Triple
T24194240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premier League 2009–10 |
E599783
|
entity |
| Predicate | mostGoalsByTeamNumber |
P9098
|
FINISHED |
| Object | 103 |
—
|
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: 103 | Statement: [Premier League 2009–10, mostGoalsByTeamNumber, 103]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mostGoalsByTeamNumber Context triple: [Premier League 2009–10, mostGoalsByTeamNumber, 103]
-
A.
topScorerTeam
Indicates that a given team is the one with the highest score (or total points) in a particular game, season, or competition.
-
B.
goalScorerTeam
Indicates that a team is the one for which a particular goal scorer scored a goal.
-
C.
numberOfGoals
chosen
Indicates the total count of goals scored or achieved by an entity in a given context.
-
D.
mostWinsGoaltenderTeam
Indicates that a team is the one for which a given goaltender has recorded the highest number of wins.
-
E.
fewestGoalsTeam
Indicates the team that has conceded or scored the lowest number of goals compared to all other teams in the relevant context.
- 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_69e288cdc8b88190bf2f835d3cb4ca28 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e24947948190b609a39a2b8828ad |
completed | April 29, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.