Triple
T6088717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hippodrome de Longchamp |
E135702
|
entity |
| Predicate | hasMultipleCourses |
P68045
|
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: [Hippodrome de Longchamp, hasMultipleCourses, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMultipleCourses Context triple: [Hippodrome de Longchamp, hasMultipleCourses, yes]
-
A.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
B.
hasPrimaryCourse
Indicates that an entity is associated with its main or principal course in a given context (such as a meal, curriculum, or sequence of offerings).
-
C.
hasCoursePattern
Indicates that an entity follows, is associated with, or is defined by a particular course structure or pattern.
-
D.
numberOfCourses
Indicates the quantity of courses associated with a given entity.
-
E.
hasStudents
Indicates that an entity (such as a class, school, or teacher) is associated with one or more students.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057a6f7588190b265d6005fbaf6b3 |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8e3f2c8190be459ca02f9b315a |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:12 p.m.