Triple
T36716838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Lopez |
E906933
|
entity |
| Predicate | designedGolfCourse |
P128695
|
FINISHED |
| Object | Nancy Lopez Legacy Golf & Country Club |
—
|
NE NERFINISHED |
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: Nancy Lopez Legacy Golf & Country Club | Statement: [Nancy Lopez, designedGolfCourse, Nancy Lopez Legacy Golf & Country Club]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: designedGolfCourse Context triple: [Nancy Lopez, designedGolfCourse, Nancy Lopez Legacy Golf & Country Club]
-
A.
designedGolfCourses
chosen
Indicates that one entity is the architect or creator responsible for designing the layout and features of one or more golf courses associated with another entity.
-
B.
golfCourseUse
Indicates that an entity is used as a golf course or for playing golf.
-
C.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
D.
golfCourseStyle
Indicates the design or architectural style that characterizes a particular golf course.
-
E.
golfCourseSetting
Indicates that an entity is set in, located at, or contextually associated with a golf course.
- 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_69f76e73ad108190a5241585f2303e9a |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff5803c02c81908b63067119f5e684 |
completed | May 9, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69ff576d8b308190b49a1e072a0ae661 |
completed | May 9, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:12 p.m.