Triple
T2248636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sidney Crosby |
E49563
|
entity |
| Predicate | scoredFamousGoal |
P2695
|
FINISHED |
| Object | 2010 Olympic gold medal overtime goal vs United States |
—
|
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: 2010 Olympic gold medal overtime goal vs United States | Statement: [Sidney Crosby, scoredFamousGoal, 2010 Olympic gold medal overtime goal vs United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredFamousGoal Context triple: [Sidney Crosby, scoredFamousGoal, 2010 Olympic gold medal overtime goal vs United States]
-
A.
goalScorer
chosen
Indicates that the subject is the player who scored a particular goal in a game or match.
-
B.
topScorer
Indicates that the subject is the individual with the highest score among a specified group or in a particular context.
-
C.
scoredFor
Indicates that one entity achieved points or a score on behalf of another entity, such as a player scoring for a team.
-
D.
ownGoalBy
Indicates that a goal was accidentally scored against a team by the specified player (i.e., the player scored an own goal).
-
E.
FIFABallonDorWinner
Indicates that the subject is the football player who won the FIFA Ballon d'Or award in the specified year or 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ed5c38819080b45ea398fb59f2 |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.