Triple
T23954899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rogers Hornsby |
E603757
|
entity |
| Predicate | tripleCrownSeasons |
P154498
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Rogers Hornsby, tripleCrownSeasons, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tripleCrownSeasons Context triple: [Rogers Hornsby, tripleCrownSeasons, 2]
-
A.
yearsSincePreviousTripleCrown
Indicates the number of years that have elapsed since the most recent prior occurrence of a Triple Crown.
-
B.
tripleCrownWinner
Indicates that an entity has won all three major titles or championships that together constitute a "Triple Crown" within a particular sport or competitive domain.
-
C.
tripleCrownYear
Indicates the year in which an entity achieved a Triple Crown title or completed a Triple Crown accomplishment.
-
D.
previousTripleCrownWinner
Indicates that one entity is the Triple Crown winner who immediately preceded the other entity in time.
-
E.
previousTripleCrownYear
Indicates that the subject year is the most recent year before the object year in which a Triple Crown (e.g., in horse racing) was achieved.
- 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_69e2954222288190a7323554d0cca8d7 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d0d616ec81908c796894f40f3015 |
completed | April 29, 2026, 9:35 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:21 p.m.