Triple
T6075195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany women's national football team |
E135382
|
entity |
| Predicate | worldCupRunnersUp |
P65536
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Germany women's national football team, worldCupRunnersUp, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldCupRunnersUp Context triple: [Germany women's national football team, worldCupRunnersUp, 1]
-
A.
worldCupRunnerUp
Indicates that an entity finished in second place in a FIFA World Cup tournament.
-
B.
worldCupRunnersUpYear
Indicates the year in which a given team finished as runners-up in the FIFA World Cup tournament.
-
C.
worldCupRunnersUpFinishes
chosen
Indicates the number of times an entity has finished as the runner-up in the FIFA World Cup.
-
D.
fifaWorldCupRunnersUpYear
Indicates the year in which an entity finished as runners-up in a FIFA World Cup tournament.
-
E.
RugbyWorldCupRunnersUp
Indicates the relationship where a team is the runner-up (finishes in second place) in a Rugby World Cup tournament.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0575d4ed481908eddc88e9b90e22f |
completed | March 22, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:11 p.m.