Triple
T12381922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Coast Sports Stadium |
E295764
|
entity |
| Predicate | hasTrainingPitch |
P104664
|
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: [Cape Coast Sports Stadium, hasTrainingPitch, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingPitch Context triple: [Cape Coast Sports Stadium, hasTrainingPitch, yes]
-
A.
hasTrainingTrack
Indicates that an entity is associated with or assigned to a specific training track or program.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
C.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
D.
hasTrainingComplex
Indicates that an entity possesses or is associated with a dedicated facility or complex used for training activities.
-
E.
hasTrainingType
Indicates that an entity is associated with or characterized by a specific type or category of training.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbb3a2481908c2fcb5e6488eb3c |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93fa244148190a960be3ff6f1cf45 |
completed | April 10, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:54 p.m.