Triple
T17546398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tura Beach |
E427333
|
entity |
| Predicate | golfCourseSetting |
P127868
|
FINISHED |
| Object | coastal bushland |
—
|
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: coastal bushland | Statement: [Tura Beach, golfCourseSetting, coastal bushland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: golfCourseSetting Context triple: [Tura Beach, golfCourseSetting, coastal bushland]
-
A.
countryClubSetting
Indicates a setting or context that takes place within or is characteristic of a country club environment.
-
B.
golfCourseUse
Indicates that an entity is used as a golf course or for playing golf.
-
C.
golfCourseStyle
Indicates the design or architectural style that characterizes a particular golf course.
-
D.
golfCoursePar
Indicates the standard number of strokes a skilled golfer is expected to take to complete a particular golf course or hole.
-
E.
golfCourseRestored
Indicates that a golf course has been returned to a previous or improved condition, typically after damage, neglect, or alteration.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45461643881909b106bafb89253b3 |
completed | April 19, 2026, 4:04 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fb39948190a82a597c5bac5c57 |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:49 a.m.