Triple
T21791904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muirfield |
E537990
|
entity |
| Predicate | hasCourseLayoutFeature |
P82715
|
FINISHED |
| Object | two concentric loops of nine holes |
—
|
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 concentric loops of nine holes | Statement: [Muirfield, hasCourseLayoutFeature, two concentric loops of nine holes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseLayoutFeature Context triple: [Muirfield, hasCourseLayoutFeature, two concentric loops of nine holes]
-
A.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
B.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
C.
hasCourseCharacteristic
chosen
Indicates that a course possesses or is associated with a particular characteristic, feature, or attribute.
-
D.
hasEducationalFeature
Indicates that something includes or is associated with a component, characteristic, or functionality intended for educational purposes.
-
E.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
- 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_69e0c47198f881908cb0d237266c10e9 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f06220bbe0819091cf3b41aa788cc3 |
completed | April 28, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
Created at: April 16, 2026, 6:52 p.m.