Triple
T26759379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Roja |
E674757
|
entity |
| Predicate | CopaAmerica2016HostCountry |
P161483
|
FINISHED |
| Object | United States |
—
|
NE NERFINISHED |
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: United States | Statement: [La Roja, CopaAmerica2016HostCountry, United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CopaAmerica2016HostCountry Context triple: [La Roja, CopaAmerica2016HostCountry, United States]
-
A.
copaAmerica2015Host
Indicates that the subject is the country or entity that hosted the 2015 Copa América tournament.
-
B.
copaAmerica2016FinalResult
Indicates the outcome or final score of the Copa América 2016 championship match between the competing teams.
-
C.
ConfederationsCupHostCity
Indicates that a city served as a host location for matches of the FIFA Confederations Cup tournament.
-
D.
worldCupHost
Indicates that one entity serves as the host country or location for a particular FIFA World Cup tournament.
-
E.
wonRecopaSudamericana
Indicates that one entity has won the Recopa Sudamericana football competition.
- F. None of above. chosen
Provenance (4 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f618dafb6c8190b4f53a7fcbf967e3 |
completed | May 2, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
| PDg | Predicate description generation | batch_69f6142a0b988190b404d078f73c3cb9 |
completed | May 2, 2026, 3:11 p.m. |
Created at: April 27, 2026, 3:57 a.m.