Triple
T4325026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNESCO European Region states |
E96616
|
entity |
| Predicate | hasLanguageDiversity |
P16608
|
FINISHED |
| Object | multilingual |
—
|
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: multilingual | Statement: [UNESCO European Region states, hasLanguageDiversity, multilingual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageDiversity Context triple: [UNESCO European Region states, hasLanguageDiversity, multilingual]
-
A.
languageDiversity
chosen
Indicates the degree to which multiple distinct languages are present and used within a given context or population.
-
B.
hasLanguageCommunity
Indicates that an entity is associated with or serves a particular language community.
-
C.
isMulticulturalCity
Indicates that a city is characterized by the presence and interaction of multiple cultural, ethnic, or linguistic communities.
-
D.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
E.
hasDistinctCulturalHeritage
Indicates that an entity possesses a unique cultural background, traditions, or practices that distinguish it from other entities.
- 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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3512ec18481908a7b5c29b3902b53 |
completed | March 12, 2026, 11:50 p.m. |
| PD | Predicate disambiguation | batch_69b34f4bec888190987fc2631498b637 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:13 p.m.