Triple
T27143738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryanair Chase |
E681882
|
entity |
| Predicate | racecourseConfiguration |
P55669
|
FINISHED |
| Object | undulating |
—
|
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: undulating | Statement: [Ryanair Chase, racecourseConfiguration, undulating]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racecourseConfiguration Context triple: [Ryanair Chase, racecourseConfiguration, undulating]
-
A.
racecourseSetting
Indicates that an event, scene, or activity takes place in the context or environment of a racecourse.
-
B.
racecourseFeature
chosen
Indicates that one entity is a physical or functional feature or component of a racecourse associated with the other entity.
-
C.
racecourseManaged
Indicates that one entity is responsible for operating, organizing, or overseeing the management of a racecourse for another entity.
-
D.
racecourseType
Indicates the specific kind or classification of a racecourse associated with an entity.
-
E.
racecourseUsed
Indicates that a particular racecourse is utilized or employed for a given event, activity, or purpose.
- 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f624c3e4bc8190af9a5d9b3c30d117 |
completed | May 2, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 9:10 a.m.