Triple
T37261171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Σικελία |
E924261
|
entity |
| Predicate | έχει επίσημη γλώσσα |
P236
|
FINISHED |
| Object | ιταλικά |
—
|
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: ιταλικά | Statement: [Σικελία, έχει επίσημη γλώσσα, ιταλικά]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: έχει επίσημη γλώσσα Context triple: [Σικελία, έχει επίσημη γλώσσα, ιταλικά]
-
A.
declaresOfficialLanguageOf
Indicates that an authority formally designates a particular language as the official language of a specified entity or jurisdiction.
-
B.
officialLanguage
chosen
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
C.
hasLanguageOfficial
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
D.
usesOfficialLanguageOf
Indicates that one entity adopts and employs the official language of another entity for communication or formal purposes.
-
E.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
- 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_69f76eabd6c481909d414a80a1345c98 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.