Triple
T17880231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish |
E447062
|
entity |
| Predicate | partiallyMutuallyIntelligibleWith |
P7448
|
FINISHED |
| Object | Swedish |
—
|
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: Swedish | Statement: [Danish, partiallyMutuallyIntelligibleWith, Swedish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partiallyMutuallyIntelligibleWith Context triple: [Danish, partiallyMutuallyIntelligibleWith, Swedish]
-
A.
areMutuallyIntelligibleToSomeDegree
chosen
Indicates that two or more languages or communication systems can be at least partially understood by each other’s users without prior learning or translation.
-
B.
lessMutuallyIntelligibleThan
Indicates that the level of mutual intelligibility between one pair of languages (or language varieties) is lower than that between another pair.
-
C.
linguisticallyRelatedTo
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
D.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
-
E.
hasLanguageFormOf
Indicates that one entity is a specific linguistic form, expression, or realization of the language used by another entity.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49c0e56bc819097649377b520de63 |
completed | April 19, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e9b77c8190bbfb508f28dfacfa |
completed | April 18, 2026, 7:18 p.m. |
Created at: April 10, 2026, 10:18 a.m.