Triple
T28299768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MUF |
E713674
|
entity |
| Predicate | nameAcronymLanguage |
P43870
|
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: [MUF, nameAcronymLanguage, Swedish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameAcronymLanguage Context triple: [MUF, nameAcronymLanguage, Swedish]
-
A.
hasAcronymVariantLanguage
Indicates that a language has an alternative form represented as an acronym variant.
-
B.
acronymOfNativeName
Indicates that one term is an acronym formed from the native-language version of another name.
-
C.
hasAcronymExpansionLanguage
chosen
Indicates that a specified language is the language in which an acronym’s full expansion is expressed.
-
D.
commonAbbreviationLanguage
Indicates that one language is commonly abbreviated or represented by another language or code in written or symbolic form.
-
E.
alternateLanguageName
Indicates that an entity has an additional name or label in a different language from its primary or default name.
- 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_69efb524ab688190a1ce7ee7c9520932 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f644b1f4448190896e0b0d5cbc6872 |
completed | May 2, 2026, 6:38 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:34 p.m.