Triple
T16797612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glen Golf Club |
E408273
|
entity |
| Predicate | hasApproximatePar |
P9773
|
FINISHED |
| Object | 71 |
—
|
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: 71 | Statement: [Glen Golf Club, hasApproximatePar, 71]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximatePar Context triple: [Glen Golf Club, hasApproximatePar, 71]
-
A.
hasApproximateUse
Indicates that one entity is used for a purpose that is similar to, but not exactly the same as, the use or function of another entity.
-
B.
hasApproximateValue
chosen
Indicates that one entity’s value is close to, but not exactly equal to, the value of another entity within an acceptable margin of error.
-
C.
holdsApproximatelyFor
Indicates that a condition, relation, or value is valid only to an approximate degree or within a tolerance, rather than holding exactly.
-
D.
hasApproximateShape
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of another entity.
-
E.
containsApproximately
Indicates that one entity holds or includes another entity in a quantity or proportion that is close to, but not exactly, a specified amount.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2ab08e8819097072a23c4a62392 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319d0fdb8819088425bd82431640f |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.