Triple
T17111474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Cuba |
E415234
|
entity |
| Predicate | sinisterBaseFieldDepicts |
P125985
|
FINISHED |
| Object | Cuban landscape with palm tree |
—
|
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: Cuban landscape with palm tree | Statement: [Coat of arms of Cuba, sinisterBaseFieldDepicts, Cuban landscape with palm tree]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sinisterBaseFieldDepicts Context triple: [Coat of arms of Cuba, sinisterBaseFieldDepicts, Cuban landscape with palm tree]
-
A.
holdsInSinisterPaw
Indicates that an entity is holding another entity in its left (sinister) paw.
-
B.
liesBeyond
Indicates that one entity is located at a greater distance or outside the boundary of another reference point, region, or limit.
-
C.
liesToThe
Indicates that one entity intentionally provides false or misleading information to another entity.
-
D.
viewOfSin
Indicates a person's attitude, interpretation, or judgment about what constitutes sin or sinful behavior.
-
E.
typicallyDepicts
Indicates that one entity is most commonly or characteristically portrayed or represented by the other in depictions or images.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2a7f2c81908eb19594b6accab7 |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:35 a.m.