Triple
T342427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Course at St Andrews |
E6864
|
entity |
| Predicate | standardRoundLength |
P12056
|
FINISHED |
| Object | 18 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: 18 holes | Statement: [Old Course at St Andrews, standardRoundLength, 18 holes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: standardRoundLength Context triple: [Old Course at St Andrews, standardRoundLength, 18 holes]
-
A.
standardNumber
Indicates that an entity is associated with a canonical or officially recognized reference number used for identification or classification.
-
B.
round
Indicates that an entity has a circular or approximately circular shape or form.
-
C.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
D.
standardTimeCounterpart
Indicates that one time representation is the corresponding value expressed in a standard or canonical time format for the other.
-
E.
baseCircumference
Indicates the circumference measurement of the base of an object or geometric figure.
- 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.