Triple
T3070707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal St George’s Golf Club |
E64012
|
entity |
| Predicate | hasCourseLengthYards |
P34478
|
FINISHED |
| Object | 7204 |
—
|
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: 7204 | Statement: [Royal St George’s Golf Club, hasCourseLengthYards, 7204]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCourseLengthYards Context triple: [Royal St George’s Golf Club, hasCourseLengthYards, 7204]
-
A.
hasYardage
chosen
Indicates that something possesses or is associated with a specific measured distance or length, typically expressed in yards.
-
B.
courseLength
Indicates the duration or total length of a course, typically measured in units such as hours, weeks, or credits.
-
C.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
D.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
E.
hasDegreeLength
Indicates that something possesses a length measured in degrees, typically expressing angular extent or size.
- 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_69ad857a8aec8190bfdfd9c14554ac5a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada14b366881908e2ca104e5f38251 |
completed | March 8, 2026, 4:18 p.m. |
| PD | Predicate disambiguation | batch_69ad9625b30c819099ef9349c91d7b25 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:02 p.m.