Triple
T4412914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thunder Snow |
E94891
|
entity |
| Predicate | racedAsThreeYearOld |
P55502
|
FINISHED |
| Object | 2017 |
—
|
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: 2017 | Statement: [Thunder Snow, racedAsThreeYearOld, 2017]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racedAsThreeYearOld Context triple: [Thunder Snow, racedAsThreeYearOld, 2017]
-
A.
tripleCrownYear
Indicates the year in which an entity achieved a Triple Crown title or completed a Triple Crown accomplishment.
-
B.
raceYear
Indicates the specific calendar year in which a particular race event takes place.
-
C.
hasRacecourse
Indicates that an entity possesses, contains, or is associated with a racecourse facility or track.
-
D.
tripleCrownStatus
Indicates whether an entity has achieved, is pursuing, or holds a specific standing related to a recognized "triple crown" set of three major accomplishments or titles.
-
E.
thirdHorseColor
Indicates that the relationship specifies the color of the third horse in a given ordered group of horses.
- 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_69b34539638c8190abfea3eb29425210 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b354e7b30c819082ee781dd202dcc4 |
completed | March 13, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.