Triple
T5209887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinandega, Nicaragua |
E117604
|
entity |
| Predicate | demographicDemonym |
P191
|
FINISHED |
| Object | chinandegano |
—
|
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: chinandegano | Statement: [Chinandega, Nicaragua, demographicDemonym, chinandegano]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicDemonym Context triple: [Chinandega, Nicaragua, demographicDemonym, chinandegano]
-
A.
relatedDemonym
Indicates that one entity is the demonym (name for residents or natives) associated with the other entity.
-
B.
populationDemonym
Indicates the term used to refer to the people or inhabitants associated with a particular place or region.
-
C.
hasDemonym
chosen
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
D.
demographicsDescriptor
Indicates a descriptive attribute or classification that characterizes the demographic properties of an entity or group.
-
E.
demographicCharacteristic
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
- 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_69bd4464ba3c8190bc16b2ebbe42ddb0 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a703e388190845dedd17252ddde |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.