Triple
T21727605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peters Township |
E536312
|
entity |
| Predicate | hasPublicGolfCourse |
P4286
|
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: [Peters Township, hasPublicGolfCourse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPublicGolfCourse Context triple: [Peters Township, hasPublicGolfCourse, yes]
-
A.
hasGolfCourse
chosen
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
B.
hasGolfCourseCluster
Indicates that an entity is associated with or contains a group or concentration of golf courses in a particular area.
-
C.
hasCountryClubLocation
Indicates that a country club is located at, or associated with, a specific geographic place or address.
-
D.
hasGolfDestination
Indicates that one entity serves as a golf-related destination or location for another entity.
-
E.
numberOfGolfCourses
Indicates the total count of golf courses associated with a given entity.
- 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_69e0c46d3284819099a4f9d5a704eb95 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69effd03c6ec8190a2f0445c1f3a45b4 |
completed | April 28, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e6969725bc81908e7ad19619ba2688 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:48 p.m.