Triple
T19917780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acorn Stakes |
E478708
|
entity |
| Predicate | raceTypeByAgeSex |
P48792
|
FINISHED |
| Object | three-year-old fillies stakes |
—
|
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: three-year-old fillies stakes | Statement: [Acorn Stakes, raceTypeByAgeSex, three-year-old fillies stakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceTypeByAgeSex Context triple: [Acorn Stakes, raceTypeByAgeSex, three-year-old fillies stakes]
-
A.
raceTypeByAge
chosen
Indicates that the type or category of a race is determined or classified based on the ages of its participants.
-
B.
raceTypeBySex
Indicates that a race or competition is categorized or defined based on the sex of its participants.
-
C.
raceTypeDetail
Indicates the specific category or classification of a race, providing detailed information about the type of race involved in the relationship.
-
D.
raceCategory
Indicates the classification of an entity into a specific race or racial group within a defined categorization system.
-
E.
raceTypeStrength
Indicates the degree or category of physical or competitive strength associated with a particular race type in the relationship.
- F. None of above.
Provenance (3 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65995bd60819097cfad003dd29731 |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.