Triple
T22492365
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silver Boot goalscoring award |
E556050
|
entity |
| Predicate | rankingRelativeToGoldenBoot |
P103031
|
FINISHED |
| Object | below Golden Boot |
—
|
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: below Golden Boot | Statement: [Silver Boot goalscoring award, rankingRelativeToGoldenBoot, below Golden Boot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankingRelativeToGoldenBoot Context triple: [Silver Boot goalscoring award, rankingRelativeToGoldenBoot, below Golden Boot]
-
A.
numberOfGoldenBootAwards
Indicates the count of Golden Boot awards that an entity has received.
-
B.
yearWonGoldenBootAward
Indicates the specific year in which an entity received the Golden Boot award.
-
C.
FIFAWorldCupGoalsRank
Indicates the ranking of entities based on the number of goals they have scored in FIFA World Cup competitions.
-
D.
rankedBy
Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
-
E.
rankingPositions
chosen
Indicates the ordered placement or level assigned to entities within a ranking or hierarchy.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb01b3481908a9143503b75167f |
completed | April 29, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e898be31448190be5ae7f5656f0497 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:49 p.m.