Triple
T23750675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Weiskopf |
E586954
|
entity |
| Predicate | bestFinishAtU.S.Open |
P146253
|
FINISHED |
| Object | 2nd 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: 2nd place | Statement: [Tom Weiskopf, bestFinishAtU.S.Open, 2nd place]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFinishAtU.S.Open Context triple: [Tom Weiskopf, bestFinishAtU.S.Open, 2nd place]
-
A.
grandSlamBestResultUSOpen
Indicates the best performance or highest round an entity has achieved specifically at the US Open tennis Grand Slam tournament.
-
B.
wonUSOpen
Indicates that one entity achieved victory in the US Open competition or tournament over another entity or in a given year.
-
C.
runnerUpFinishesAtUsOpen
chosen
Indicates that an entity finished in second place (as runner-up) at the US Open in a given event or year.
-
D.
numberOfUSOpenChampionshipsWon
Indicates the count of US Open Championship titles that an entity has won.
-
E.
bestFinishInTheOpenChampionship
Indicates the highest (best) finishing position an entity has ever achieved in The Open Championship golf 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_69e2490a0eec81908cdef8a862828d7a |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcc1d4e8819099d3b4136f28f0c6 |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:13 p.m.