Triple
T6017826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Wondolowski |
E133988
|
entity |
| Predicate | individualAward |
P11
|
FINISHED |
| Object | MLS Golden Boot |
E181684
|
NE 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: MLS Golden Boot | Statement: [Chris Wondolowski, individualAward, MLS Golden Boot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MLS Golden Boot Context triple: [Chris Wondolowski, individualAward, MLS Golden Boot]
-
A.
MLS Golden Boot
chosen
The MLS Golden Boot is Major League Soccer’s annual award given to the league’s top goal scorer in the regular season.
-
B.
Golden Boot
The Golden Boot is a football award given to the top goal scorer at major tournaments, including the FIFA Club World Cup.
-
C.
Golden Boot Award
The Golden Boot Award is an international rugby league honor presented annually to the player judged to be the best in the world.
-
D.
Golden Boot Award
The Golden Boot Award is an honor recognizing significant contributions to the Western genre in film and television, often awarded to actors, directors, and other industry figures.
-
E.
FIFA World Cup Golden Boot
The FIFA World Cup Golden Boot is the award given to the tournament's top goal scorer.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008742a5c8190b9cb9c2787a3d8b3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f8458588190a78aa32cbdbecfb1 |
completed | March 22, 2026, 8:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c13564c2088190847cde0b9ec02591 |
completed | March 23, 2026, 12:43 p.m. |
Created at: March 22, 2026, 4:07 p.m.