Triple
T16515229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travers Stakes |
E401164
|
entity |
| Predicate | hasGradeStatus |
P123843
|
FINISHED |
| Object | Grade I |
—
|
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: Grade I | Statement: [Travers Stakes, hasGradeStatus, Grade I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGradeStatus Context triple: [Travers Stakes, hasGradeStatus, Grade I]
-
A.
hasGrades
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
-
B.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
C.
hasGradesOrClasses
Indicates that an entity is associated with academic evaluations or enrolled instructional sessions, such as grades received or classes taken.
-
D.
hasGradeType
Indicates that an entity is associated with a particular category or type of grade (e.g., letter grade, pass/fail, percentage).
-
E.
hasNoGrades
Indicates that an entity does not possess any recorded grades or evaluations.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e7bbfa481909037148cdb4d8996 |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296995d388190b88ebe189dce890d |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:14 a.m.