Triple
T30323312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2021 Copa América |
E771263
|
entity |
| Predicate | originallyScheduledHostCountries |
P99507
|
FINISHED |
| Object | Argentina |
—
|
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: Argentina | Statement: [2021 Copa América, originallyScheduledHostCountries, Argentina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originallyScheduledHostCountries Context triple: [2021 Copa América, originallyScheduledHostCountries, Argentina]
-
A.
originallyScheduledHostCountry
chosen
Indicates the country that was first designated to host a particular event or activity before any later changes or relocations.
-
B.
eventHostCountries
Indicates that the subject countries serve as hosts for a particular event or set of events.
-
C.
notableHostCountries
Indicates that certain countries are recognized as prominent or significant locations for hosting a particular event, activity, or entity.
-
D.
mainHostCountries
Indicates the countries that primarily host or serve as the main locations for a given entity, event, or activity.
-
E.
initialHostCountries
Indicates the countries that first hosted or received a given entity, event, or activity at its outset.
- 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_69f22489ee8481909344649bfbb92e83 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a00262d71488190a769783fb09e5803 |
completed | May 10, 2026, 6:31 a.m. |
| PD | Predicate disambiguation | batch_6a0023985f148190a335a3fb93e9981e |
completed | May 10, 2026, 6:20 a.m. |
Created at: April 29, 2026, 7:52 p.m.