Triple
T27932640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Benteke |
E708023
|
entity |
| Predicate | nationalTeamCountry |
P38099
|
FINISHED |
| Object | Belgium |
—
|
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: Belgium | Statement: [Christian Benteke, nationalTeamCountry, Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTeamCountry Context triple: [Christian Benteke, nationalTeamCountry, Belgium]
-
A.
nationalTeamFor
Indicates that one entity serves as the national team representing another entity, typically a country or nation, in a given sport or activity.
-
B.
nationalTeamSport
Indicates that a particular sport is officially designated as the national team sport of a given country or region.
-
C.
nationalTeamType
Indicates the specific category or level of a national team (e.g., senior, youth, futsal) with which an entity is associated.
-
D.
nationalTeamCode
Indicates the code that identifies the national team associated with an entity.
-
E.
countryOfTeam
chosen
Indicates that a team is associated with or represents a particular country.
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f70e8755a48190931eaa77946f9460 |
completed | May 3, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69f70abc00848190a1c3f495ef6c8dc6 |
completed | May 3, 2026, 8:43 a.m. |
Created at: April 27, 2026, 7:03 p.m.