Triple
T7202262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose City Golf Course |
E148575
|
entity |
| Predicate | hasPuttingGreen |
P75785
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Rose City Golf Course, hasPuttingGreen, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPuttingGreen Context triple: [Rose City Golf Course, hasPuttingGreen, yes]
-
A.
hasWaterHazards
Indicates that the subject contains or is associated with one or more water-based obstacles or danger areas.
-
B.
typicalWinningScoreRelativeToPar
Indicates the usual or expected winning score in relation to the course’s par (e.g., how many strokes under or over par typically wins).
-
C.
hasGolfCourse
Indicates that one entity possesses, contains, or includes a golf course as part of its facilities or attributes.
-
D.
hasGrassTypeGreens
Indicates that something possesses or includes green vegetation or grassy plant material.
-
E.
notableHole
Indicates that an entity has a hole or opening that is significant or noteworthy in some context.
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e94a9ee4819086de79fcdfa1836a |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69c6e8fd9b848190b2b1beea5698422b |
completed | March 27, 2026, 8:30 p.m. |
Created at: March 27, 2026, 2:52 p.m.