Triple
T29888161
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dani Alves |
E759071
|
entity |
| Predicate | nationalTeamHonour |
P184002
|
FINISHED |
| Object | Copa América 2007 winner with Brazil |
—
|
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: Copa América 2007 winner with Brazil | Statement: [Dani Alves, nationalTeamHonour, Copa América 2007 winner with Brazil]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nationalTeamHonour Context triple: [Dani Alves, nationalTeamHonour, Copa América 2007 winner with Brazil]
-
A.
teamHonour
Indicates that a team has received or been awarded a particular honour, title, or distinction.
-
B.
nationalTeamChampionships
Indicates the number of championship titles an entity has won at the national team level.
-
C.
teamHonors
Indicates that a team has received a particular honor, award, or title.
-
D.
nationalTeamHonourWithItaly
Indicates that an entity has received a national team honor while representing Italy.
-
E.
nationalTeamType
Indicates the specific category or level of a national team (e.g., senior, youth, futsal) with which an entity is associated.
- 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_69f2245de2f48190a481404896b56254 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 29, 2026, 6:01 p.m.