Triple
T13855907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chantilly Racecourse |
E333061
|
entity |
| Predicate | hasStraightCourse |
P111788
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Chantilly Racecourse, hasStraightCourse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStraightCourse Context triple: [Chantilly Racecourse, hasStraightCourse, yes]
-
A.
hasStraightCourseDistance
Indicates that a route or path has a specified distance measured along its straight, unobstructed course.
-
B.
hasStartFinishStraight
Indicates that something includes a straight segment that serves as both the starting and finishing section of a course or track.
-
C.
isMostlyStraight
Indicates that an entity is predominantly but not entirely straight in orientation, alignment, or form.
-
D.
hasStraightLines
Indicates that the related entity possesses or is characterized by straight, non-curved lines.
-
E.
circuitHasLongStraight
Indicates that a circuit includes at least one long, uninterrupted straight section.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02db9c9c81909bb2d2fbfb7394b1 |
completed | April 14, 2026, 9:03 a.m. |
| PD | Predicate disambiguation | batch_69dbc8691b608190a25a7c70a366b170 |
completed | April 12, 2026, 4:29 p.m. |
| PDg | Predicate description generation | batch_69dcad0eea9881908f71e1eed9a2446b |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 10:14 p.m.