Triple
T2507537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sepp Maier |
E52618
|
entity |
| Predicate | numberOfClubAppearances |
P13108
|
FINISHED |
| Object | over 500 for Bayern Munich |
—
|
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: over 500 for Bayern Munich | Statement: [Sepp Maier, numberOfClubAppearances, over 500 for Bayern Munich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfClubAppearances Context triple: [Sepp Maier, numberOfClubAppearances, over 500 for Bayern Munich]
-
A.
clubAppearances
chosen
Indicates the number of official matches a player has played for a particular club.
-
B.
playoffAppearances
Indicates the number of times an entity (such as a team or player) has qualified for and participated in postseason playoff competition.
-
C.
hasBowlAppearances
Indicates that an entity has participated in one or more bowl game appearances.
-
D.
teamPlayedFor
Indicates that a person was a member of and played for a particular sports team.
-
E.
fifaWorldCupAppearances
Indicates the number of times an entity has participated in FIFA World Cup tournaments.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.