Triple
T1443268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Águilas del América |
E31120
|
entity |
| Predicate | associatedWithCountryLeagueSystem |
P14340
|
FINISHED |
| Object | Mexican football league system |
—
|
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: Mexican football league system | Statement: [Águilas del América, associatedWithCountryLeagueSystem, Mexican football league system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithCountryLeagueSystem Context triple: [Águilas del América, associatedWithCountryLeagueSystem, Mexican football league system]
-
A.
countryLeagueSystem
chosen
Indicates that a particular league system operates within, or is associated with, a specific country.
-
B.
fifaAffiliationCountry
Indicates that a country is affiliated with or recognized by FIFA as a member football association.
-
C.
countryOfLeague
Indicates the country in which a given league is based or officially belongs.
-
D.
associatedLeagueCodeSystem
Indicates that there is a relationship linking an entity to the code system used by a particular league.
-
E.
homeCountryLeagueLevel
Indicates the competitive tier or division level of the league in the subject’s home country with which the subject is associated.
- 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_69a4991633388190a4d61b5a98aa407a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c55714588190a95b4f677c21cbaa |
completed | March 1, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69a4c47a840c819083307a65c027a19e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.