Triple
T8754185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statute of Autonomy of Catalonia |
E208033
|
entity |
| Predicate | recognizesLanguage |
P238
|
FINISHED |
| Object | Catalan |
—
|
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: Catalan | Statement: [Statute of Autonomy of Catalonia, recognizesLanguage, Catalan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recognizesLanguage Context triple: [Statute of Autonomy of Catalonia, recognizesLanguage, Catalan]
-
A.
recognizesLanguages
Indicates that an entity has the ability to identify, understand, or acknowledge one or more languages.
-
B.
recognizedLanguage
chosen
Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
-
C.
testLanguage
Indicates that an entity uses or is associated with a particular language for testing or evaluation purposes.
-
D.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69ca835cd6b08190bd7c63db92f53c86 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dd714dc8190bccc4d52f988958d |
completed | March 31, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69cc5c160dac8190b4aeb4bf0529de52 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:39 p.m.