Triple
T10150085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Gómez |
E232610
|
entity |
| Predicate | sportNumberOfTeamsPlayedFor |
P41025
|
FINISHED |
| Object | multiple professional clubs in Argentina and the United States |
—
|
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: multiple professional clubs in Argentina and the United States | Statement: [Christian Gómez, sportNumberOfTeamsPlayedFor, multiple professional clubs in Argentina and the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportNumberOfTeamsPlayedFor Context triple: [Christian Gómez, sportNumberOfTeamsPlayedFor, multiple professional clubs in Argentina and the United States]
-
A.
sportNumberOfAppearances
Indicates the total number of times an entity has participated in or appeared in a particular sport or sporting event.
-
B.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
C.
sportNumberOfClubs
chosen
Indicates the number of clubs or teams an entity is associated with in a sports context.
-
D.
leagueOfTeamPlayedFor
Indicates the league or competition in which a given team, that an entity played for, participated.
-
E.
leagueAppearances
Indicates the number of times an entity has participated in official league matches or competitions.
- 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_69ca84885e48819088a31b127cf44904 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec03e80c81909c813dae91c56272 |
completed | April 2, 2026, 4:09 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba4f5d88190ba68e63be10b08c7 |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:08 p.m.