Triple
T18044651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Run for the Black-Eyed Susans |
E431739
|
entity |
| Predicate | usualScheduling |
P3309
|
FINISHED |
| Object | two weeks after the Kentucky Derby |
—
|
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: two weeks after the Kentucky Derby | Statement: [The Run for the Black-Eyed Susans, usualScheduling, two weeks after the Kentucky Derby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usualScheduling Context triple: [The Run for the Black-Eyed Susans, usualScheduling, two weeks after the Kentucky Derby]
-
A.
typicalSchedule
chosen
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
B.
scheduledDuring
Indicates that one event or activity is planned to occur within the time interval defined by another event or period.
-
C.
schedulePattern
Indicates a recurring or structured timing relationship that defines when an event or action is scheduled to occur.
-
D.
ordinary
Indicates that something or someone is typical, usual, or not special or exceptional in the relevant context.
-
E.
scheduleUS
Indicates that an entity arranges or assigns a time for something specifically within the context of the United States.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff13f488190993445769551c9c2 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.