Triple
T7875213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Windsor Racecourse |
E182833
|
entity |
| Predicate | hasApproximateCourseLength |
P69213
|
FINISHED |
| Object | about 1 mile 4 furlongs |
—
|
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: about 1 mile 4 furlongs | Statement: [Windsor Racecourse, hasApproximateCourseLength, about 1 mile 4 furlongs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateCourseLength Context triple: [Windsor Racecourse, hasApproximateCourseLength, about 1 mile 4 furlongs]
-
A.
approximateCourseLength
chosen
Indicates an estimated or rough value for the length or duration of a course rather than an exact measurement.
-
B.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
-
C.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
D.
hasApproximateDuration
Indicates that one entity has a duration that is estimated or not exact, typically expressed as an approximate length of time.
-
E.
hasApproximateStudents
Indicates that an entity is associated with an estimated or approximate number of students, rather than an exact count.
- 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_69ca828a17248190b46defe758bc5ad3 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb39a961188190b2f12f8fe5d66641 |
completed | March 31, 2026, 3:04 a.m. |
| PD | Predicate disambiguation | batch_69cae928e1b88190b0620f4c4f03bc7d |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:57 p.m.