Triple
T23161403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhode-Saint-Genèse |
E578594
|
entity |
| Predicate | hasLanguageFacilitiesFor |
P129871
|
FINISHED |
| Object | French-speaking residents |
—
|
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: French-speaking residents | Statement: [Rhode-Saint-Genèse, hasLanguageFacilitiesFor, French-speaking residents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageFacilitiesFor Context triple: [Rhode-Saint-Genèse, hasLanguageFacilitiesFor, French-speaking residents]
-
A.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
B.
languageTypeCovered
chosen
Indicates that one entity provides coverage, support, or applicability for a particular type or category of language associated with another entity.
-
C.
languageOfImplementation
Indicates the programming language in which a given software system, component, or algorithm is implemented.
-
D.
implementedInLanguage
Indicates that a piece of software or code is written using a particular programming language.
-
E.
developedForLanguage
Indicates that something (such as a tool, system, or resource) was specifically created or adapted to be used with a particular language.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f006930819097aafef87405d737 |
completed | April 29, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:02 p.m.