Triple
T22665116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lionel Messi at Inter Miami CF |
E559762
|
entity |
| Predicate | leaguesCupGoldenBoot |
P80658
|
FINISHED |
| Object | 2023 |
—
|
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: 2023 | Statement: [Lionel Messi at Inter Miami CF, leaguesCupGoldenBoot, 2023]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leaguesCupGoldenBoot Context triple: [Lionel Messi at Inter Miami CF, leaguesCupGoldenBoot, 2023]
-
A.
yearWonGoldenBootAward
Indicates the specific year in which an entity received the Golden Boot award.
-
B.
topGoalScorerAward
chosen
Indicates that an entity receives an award for scoring the highest number of goals in a given competition or season.
-
C.
awardsCONCACAFChampionsCupBerthTo
Indicates that a CONCACAF Champions Cup qualification spot is granted to a team or entity as a result of a specific competition, achievement, or allocation process.
-
D.
leagueCup
Indicates that an entity is a cup-style competition organized within or by a specific league.
-
E.
SouthAmericanFootballerOfTheYear
Indicates that a person has been recognized as the South American Footballer of the Year, typically awarded to the best-performing football player in South America for a given year.
- 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_69e2454a158c819093b8e35f5045efb6 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1781b3dbc8190a312843cf8c1bfc6 |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:08 p.m.