Triple
T30941024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sleeping Beauty legend |
E788259
|
entity |
| Predicate | languageOfCanonicalVersion |
P19280
|
FINISHED |
| Object | German |
—
|
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: German | Statement: [Sleeping Beauty legend, languageOfCanonicalVersion, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCanonicalVersion Context triple: [Sleeping Beauty legend, languageOfCanonicalVersion, German]
-
A.
officialLanguageVersion
Indicates that one language variant is the officially recognized form or version used for formal or administrative purposes in relation to another language or context.
-
B.
primaryLanguageVersion
Indicates that one language version of a resource is designated as the main or default version among its language variants.
-
C.
canonicalLanguage
Indicates that one entity is the officially recognized or standard language associated with another entity.
-
D.
standardLanguageOf
Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
-
E.
languageOfOfficialEditions
chosen
Indicates the language in which the official editions or versions of a work, document, or publication are produced or authorized.
- 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff53389a0481908b2baeb43c6294f0 |
completed | May 9, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69ff52e2b4b88190b38d160d771fe14b |
completed | May 9, 2026, 3:29 p.m. |
Created at: April 29, 2026, 8:53 p.m.