Triple
T37361521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South American Footballer of the Year |
E927590
|
entity |
| Predicate | typicalRecipientsNationality |
P79483
|
FINISHED |
| Object | South American countries |
—
|
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: South American countries | Statement: [South American Footballer of the Year, typicalRecipientsNationality, South American countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRecipientsNationality Context triple: [South American Footballer of the Year, typicalRecipientsNationality, South American countries]
-
A.
notableRecipientNationality
Indicates that the notable recipient of something (such as an award, honor, or recognition) has a specified nationality.
-
B.
recipientNationality
Indicates that the recipient in a relationship or transaction has a specified national affiliation or citizenship.
-
C.
targetNationality
Indicates that one entity has the specified nationality as its intended or designated target.
-
D.
typicalBearersNationality
chosen
Indicates the nationality that entities of a given type or class are most commonly associated with.
-
E.
otherSignificantNationalitiesRepresented
Indicates that additional notable nationalities, beyond the primary one(s) already identified, are present or represented in the given context.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a13a1308190a202df66f4781855 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:16 p.m.