Triple
T24902779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebound Ace |
E623623
|
entity |
| Predicate | usedUntilYearAtTournament |
P157464
|
FINISHED |
| Object | 2007 Australian Open |
—
|
NE NERFINISHED |
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: 2007 Australian Open | Statement: [Rebound Ace, usedUntilYearAtTournament, 2007 Australian Open]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedUntilYearAtTournament Context triple: [Rebound Ace, usedUntilYearAtTournament, 2007 Australian Open]
-
A.
originalTournamentYear
Indicates the year in which the referenced tournament was first held or originally established.
-
B.
firstKnownTournamentYear
Indicates the year in which a tournament was first known to have been held.
-
C.
actualTournamentYear
Indicates the specific calendar year in which a given tournament actually took place.
-
D.
hasTourEndYear
Indicates the year in which a tour or touring activity concludes.
-
E.
firstUsedInTournament
Indicates that an entity (such as a move, strategy, or item) was used for the first time in a specific tournament.
- F. None of above. chosen
Provenance (4 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_69e2fac797cc8190b30d77f4121099ac |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f4303fad6c8190844f069164f0904d |
completed | May 1, 2026, 4:46 a.m. |
Created at: April 18, 2026, 5:27 a.m.