Triple
T4713812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Marino national football team |
E104581
|
entity |
| Predicate | typeOfPlayers |
P27786
|
FINISHED |
| Object | mostly part-time or amateur footballers |
—
|
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: mostly part-time or amateur footballers | Statement: [San Marino national football team, typeOfPlayers, mostly part-time or amateur footballers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfPlayers Context triple: [San Marino national football team, typeOfPlayers, mostly part-time or amateur footballers]
-
A.
typeOfTeams
Indicates the categories or kinds of teams to which an entity or group of entities belongs.
-
B.
participantType
Indicates the specific role or category that a participant has within a given event, activity, or relationship.
-
C.
typeOfAthlete
Indicates that one entity is an athlete and the other specifies the kind or category of athlete they are.
-
D.
hasProfessionalPlayers
chosen
Indicates that an entity is associated with or includes individuals who participate in a profession at a professional level.
-
E.
typeOfFootball
Indicates the specific code or variant of football that characterizes or classifies a given football-related entity.
- 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_69bd43ec4a348190bc41afae43375e71 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd680beb508190b3d74e20e1c64405 |
completed | March 20, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69bd621ddcd88190903288566f5e5dab |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.