Triple
T14929160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swilken Bridge |
E372210
|
entity |
| Predicate | courseRole |
P116704
|
FINISHED |
| Object | links fairway of 1st and 18th 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: links fairway of 1st and 18th holes | Statement: [Swilken Bridge, courseRole, links fairway of 1st and 18th holes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseRole Context triple: [Swilken Bridge, courseRole, links fairway of 1st and 18th holes]
-
A.
studentSectionRole
Indicates the specific role or capacity (e.g., participant, assistant, auditor) that a student holds within a particular course section.
-
B.
roleAtInstructure
Indicates that an entity holds a specific role or position within the organization Instructure.
-
C.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
D.
campusRole
Indicates the specific position, function, or capacity an individual holds within a campus or academic institution.
-
E.
educationPolicyRole
Indicates a role in creating, influencing, or implementing education-related policies or regulations.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded634e67881909daec9eaef188d09 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:36 a.m.