Triple
T7426990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Golden Shoe |
E171392
|
entity |
| Predicate | secondMostAwardsCount |
P2403
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [European Golden Shoe, secondMostAwardsCount, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondMostAwardsCount Context triple: [European Golden Shoe, secondMostAwardsCount, 4]
-
A.
secondRunnerUp
Indicates that one entity finished in third place in a competition or ranking relative to the others.
-
B.
isSecondHighest
chosen
Indicates that one entity ranks immediately below the highest-ranked entity within a specified ordering or set.
-
C.
isSecondLargest
Indicates that one entity has a value or size that is greater than all others except for a single larger entity, making it the second largest in the compared set.
-
D.
secondPlace
Indicates that an entity holds the position of runner-up or finishes in second place in a ranked ordering, competition, or comparison relative to others.
-
E.
secondHighestCivilianAwardIn
Indicates that an entity is the second highest-ranking civilian award conferred within a specified country or jurisdiction.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3055b7881908269ab909c5a85b5 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.