Triple
T23802222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomáš Rosický |
E588702
|
entity |
| Predicate | numberOfAppearancesForTeam |
P13109
|
FINISHED |
| Object | Czech Republic national football team:over 100 |
—
|
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: Czech Republic national football team:over 100 | Statement: [Tomáš Rosický, numberOfAppearancesForTeam, Czech Republic national football team:over 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAppearancesForTeam Context triple: [Tomáš Rosický, numberOfAppearancesForTeam, Czech Republic national football team:over 100]
-
A.
teamAppearances
Indicates the number of times an entity has participated in or been present as part of a particular team.
-
B.
nationalTeamAppearances
chosen
Indicates the number of official matches in which an entity has represented its national team.
-
C.
gameCountPerTeam
Indicates the number of games associated with or played by each team.
-
D.
sportNumberOfAppearances
Indicates the total number of times an entity has participated in or appeared in a particular sport or sporting event.
-
E.
clubAppearances
Indicates the number of official matches a player has played for a particular club.
- 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_69e25d15db58819092ac1e6791696fd9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c74f34108190b11961d634559d2b |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:53 p.m.