Triple
T26983464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rövarna i Skuleskogen |
E679666
|
entity |
| Predicate | workLanguageCode |
P115202
|
FINISHED |
| Object | sv |
—
|
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: sv | Statement: [Rövarna i Skuleskogen, workLanguageCode, sv]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workLanguageCode Context triple: [Rövarna i Skuleskogen, workLanguageCode, sv]
-
A.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
B.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
C.
workLanguageOfTitle
chosen
Indicates the language in which a specific work or title is expressed or written.
-
D.
lenguaDeTrabajo
Indicates that something functions as a working language used for communication in a specific context or setting.
-
E.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f62157d63c819096fd1addc0b960dc |
completed | May 2, 2026, 4:07 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 6:47 a.m.