Triple
T18882219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alès |
E461857
|
entity |
| Predicate | hasDemonymMasculine |
P15475
|
FINISHED |
| Object | Alésien |
—
|
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: Alésien | Statement: [Alès, hasDemonymMasculine, Alésien]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDemonymMasculine Context triple: [Alès, hasDemonymMasculine, Alésien]
-
A.
hasDemonym
Indicates that one entity is the term (demonym) used to refer to the inhabitants or natives of another entity (typically a place).
-
B.
hasDemonymLanguage
Indicates that a language is used as the demonym (people’s name or adjective of nationality) for inhabitants of a particular place or group.
-
C.
usesDemonymForm
Indicates that one entity refers to another using a demonym form, i.e., a name derived from the inhabitants or nationality associated with that entity.
-
D.
relatedDemonym
Indicates that one entity is the demonym (name for residents or natives) associated with the other entity.
-
E.
hasMasculineForm
chosen
Indicates that an entity has a corresponding masculine grammatical or lexical form.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3d2028481908af2b1560312e26c |
completed | April 20, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:57 a.m.