Triple
T32092668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina defeated France in opening match |
E819636
|
entity |
| Predicate | teamCaptainOfArgentina |
P167956
|
FINISHED |
| Object | Agustín Pichot |
—
|
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: Agustín Pichot | Statement: [Argentina defeated France in opening match, teamCaptainOfArgentina, Agustín Pichot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamCaptainOfArgentina Context triple: [Argentina defeated France in opening match, teamCaptainOfArgentina, Agustín Pichot]
-
A.
ArgentinaCaptain
chosen
Indicates that a person serves as the captain of Argentina’s national team in a particular sport or context.
-
B.
teamCoachOfArgentina
Indicates that one entity serves as the coach of the Argentina national team.
-
C.
atleticoMadridCaptain
Indicates that one entity serves as the team captain of Atlético Madrid.
-
D.
captainOfBrazil
Indicates that a person serves as the captain (team leader) of the Brazil national team.
-
E.
teamNicknameOfArgentina
Indicates the commonly used nickname or moniker that refers to the national team of Argentina.
- 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_69f349004b2481908ce2e50af0d579a8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bbbef7a88190b0affdec1d41c1e0 |
completed | May 3, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:25 a.m.