Triple
T25065303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women's British Open |
E627768
|
entity |
| Predicate | regionOfCourses |
P166567
|
FINISHED |
| Object | United Kingdom |
—
|
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: United Kingdom | Statement: [Women's British Open, regionOfCourses, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfCourses Context triple: [Women's British Open, regionOfCourses, United Kingdom]
-
A.
regionOfInstitution
Indicates that a specified region is the geographic area in which an institution is located or operates.
-
B.
studiedInRegion
Indicates that an entity pursued studies or received education within a specified geographic region.
-
C.
commonCourse
Indicates that two or more entities share at least one course in common.
-
D.
coursePar
Indicates that two entities (such as paths, lines, or trajectories) run alongside each other in the same general direction without intersecting.
-
E.
regionOfStudy
Indicates the academic or research area that is the focus of someone’s study or investigation.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f662a29b3881909957a7e3b986653c |
completed | May 2, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69f661b47d088190934f63884a203261 |
completed | May 2, 2026, 8:42 p.m. |
Created at: April 18, 2026, 6:10 a.m.