Triple
T10278443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Cunningham |
E241029
|
entity |
| Predicate | MLSGoalsRecord |
P93232
|
FINISHED |
| Object | former all-time leading goal scorer in Major League Soccer |
—
|
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: former all-time leading goal scorer in Major League Soccer | Statement: [Jeff Cunningham, MLSGoalsRecord, former all-time leading goal scorer in Major League Soccer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MLSGoalsRecord Context triple: [Jeff Cunningham, MLSGoalsRecord, former all-time leading goal scorer in Major League Soccer]
-
A.
goalsHomeTeam
Indicates the number of goals scored by the home team in a match.
-
B.
goalScorerTeam
Indicates that a team is the one for which a particular goal scorer scored a goal.
-
C.
totalGoalsRecord
Indicates the total number of goals that have been recorded for an entity across all relevant events or contexts.
-
D.
goalScorer
Indicates that the subject is the player who scored a particular goal in a game or match.
-
E.
teamAchievement
Indicates that a group of individuals collectively accomplished a shared goal or met a performance milestone.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d7ccb7ec8190a538cf279e48116e |
completed | April 7, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f117708190928f92ae2611d724 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d7cada7881908beba55a1dc9ecb9 |
completed | April 7, 2026, 10:09 a.m. |
Created at: April 6, 2026, 11:38 a.m.