Triple
T342446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Course at St Andrews |
E6864
|
entity |
| Predicate | numberOfDoubleGreens |
P12061
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Old Course at St Andrews, numberOfDoubleGreens, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDoubleGreens Context triple: [Old Course at St Andrews, numberOfDoubleGreens, 7]
-
A.
hasNumberOfArches
Indicates the relationship specifying how many arches are present in or associated with a given entity.
-
B.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
C.
branchCount
Indicates the number of branches associated with a given entity or structure.
-
D.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
E.
numberOfStripes
Indicates the count of distinct stripe markings associated with an entity.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eafef8c88190a5932eb2c6ac4a5d |
completed | Feb. 28, 2026, 1:17 p.m. |
| PD | Predicate disambiguation | batch_69a2e95197fc8190820e8ebd0d7d27fa |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0a4c448190a8a179daa9b90645 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.