Triple
T24559729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colbert Hills Golf Course |
E607617
|
entity |
| Predicate | hasTeeOptions |
P69152
|
FINISHED |
| Object | multiple sets of tees |
—
|
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: multiple sets of tees | Statement: [Colbert Hills Golf Course, hasTeeOptions, multiple sets of tees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTeeOptions Context triple: [Colbert Hills Golf Course, hasTeeOptions, multiple sets of tees]
-
A.
hasTeeType
Indicates that an entity (typically a golf hole or course) is associated with a specific type or category of tee.
-
B.
hasTeeBoxes
chosen
Indicates that a golf course or hole is equipped with one or more tee boxes from which players begin play.
-
C.
hasCaffeinatedOption
Indicates that something offers or includes at least one option that contains caffeine.
-
D.
teaType
Indicates the specific variety or category of tea associated with an entity.
-
E.
hasBeverageCategory
Indicates that an entity is associated with or classified under a particular beverage category.
- 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_69e2c4cc35a48190990b7571bc086df8 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8f57a7c8190a0eb8d6d6ef6ae61 |
completed | April 30, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.