Triple
T2341213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | US Open (tennis) |
E45029
|
entity |
| Predicate | grandSlamOrder |
P38842
|
FINISHED |
| Object | fourth of the year |
—
|
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: fourth of the year | Statement: [US Open (tennis), grandSlamOrder, fourth of the year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandSlamOrder Context triple: [US Open (tennis), grandSlamOrder, fourth of the year]
-
A.
grandSlamSinglesTitles
Indicates the number of Grand Slam singles tennis titles an entity has won.
-
B.
GrandSlams
Indicates that an entity has won or is associated with victories in major Grand Slam tournaments within a given sport.
-
C.
otherGrandSlams
Indicates that an entity is associated with Grand Slam tournaments other than a primary or specifically referenced one.
-
D.
grandSlamTournamentHosted
Indicates that a particular grand slam tennis tournament is hosted or held at a specific location or by a specific organizing entity.
-
E.
grandSlamDoublesTitles
Indicates the number of Grand Slam tennis doubles titles an entity has won.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abcade3c808190ab3803538ccbe620 |
completed | March 7, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69abc59616a8819099711834e6f1ccd6 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abcadd2a0c8190b6973d390e98bd66 |
completed | March 7, 2026, 6:51 a.m. |
Created at: March 4, 2026, 7:52 p.m.