Triple
T29374680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cuba (municipality) |
E744958
|
entity |
| Predicate | hasMunicipalParish |
P178050
|
FINISHED |
| Object | Cuba (parish) |
—
|
NE NERFINISHED |
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: Cuba (parish) | Statement: [Cuba (municipality), hasMunicipalParish, Cuba (parish)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalParish Context triple: [Cuba (municipality), hasMunicipalParish, Cuba (parish)]
-
A.
hasMunicipalDistrict
Indicates that an administrative entity includes or is divided into one or more municipal districts as its subordinate units.
-
B.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
-
C.
hasCivilParishComponent
chosen
Indicates that an entity includes or is composed of the specified civil parish as one of its administrative components.
-
D.
hasRuralParish
Indicates that an entity possesses or is associated with a rural parish as an administrative or ecclesiastical subdivision.
-
E.
hasUrbanParish
Indicates that an entity is associated with, or contains, a parish located in an urban area.
- 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_69f0a79ba954819094597628112c6091 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f79f48acec8190a9d5964581a94f6c |
completed | May 3, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69f79e4888248190be2f63cdfb5cd7b7 |
completed | May 3, 2026, 7:13 p.m. |
Created at: April 28, 2026, 2:30 p.m.