Triple
T25065304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women's British Open |
E627768
|
entity |
| Predicate | notableCourseUsed |
P21769
|
FINISHED |
| Object | St Andrews (Old Course) |
—
|
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: St Andrews (Old Course) | Statement: [Women's British Open, notableCourseUsed, St Andrews (Old Course)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCourseUsed Context triple: [Women's British Open, notableCourseUsed, St Andrews (Old Course)]
-
A.
notableCourse
Indicates that a course is particularly significant, distinguished, or noteworthy in relation to an entity (such as a person or institution).
-
B.
notableCourseType
Indicates that a course has a particular notable or distinguished type or classification (e.g., flagship, honors, or otherwise specially recognized).
-
C.
courseUse
Indicates that a course employs, incorporates, or makes use of a particular resource, tool, or material in its instruction or structure.
-
D.
usesCourse
chosen
Indicates that one entity makes use of, applies, or relies on a particular course in some context or activity.
-
E.
courseUsedSince
Indicates that a particular course has been in use or offered starting from a specified point in time.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 18, 2026, 6:10 a.m.