Triple
T16533553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Germany women's national ice hockey team |
E401626
|
entity |
| Predicate | bestWorldChampionshipFinish |
P45110
|
FINISHED |
| Object | 4th place |
—
|
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: 4th place | Statement: [Germany women's national ice hockey team, bestWorldChampionshipFinish, 4th place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestWorldChampionshipFinish Context triple: [Germany women's national ice hockey team, bestWorldChampionshipFinish, 4th place]
-
A.
bestWorldChampionshipResult
chosen
Indicates the highest (best) world championship result or placement that an entity has achieved.
-
B.
bestFinishInTheOpenChampionship
Indicates the highest (best) finishing position an entity has ever achieved in The Open Championship golf tournament.
-
C.
bestWorldCupFinish
Indicates the highest stage or ranking a team or participant has ever achieved in any edition of the World Cup.
-
D.
WorldChampionshipBestResult
Indicates the best performance or highest placement an entity has ever achieved in a world championship competition.
-
E.
bestRaceFinishPositionAchievedByDriver
Indicates the best (highest-ranking) race finishing position that a particular driver has ever achieved.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed97b0881909de106418aca8180 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.