Triple
T22455889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elbing Vocabulary |
E555113
|
entity |
| Predicate | originalLanguageOfGlosses |
P108236
|
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: [Elbing Vocabulary, originalLanguageOfGlosses, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageOfGlosses Context triple: [Elbing Vocabulary, originalLanguageOfGlosses, German]
-
A.
hasMultilingualGlosses
Indicates that an entity is associated with glosses or explanatory labels available in multiple languages.
-
B.
originalLanguageText
Indicates that a text is expressed in its original, untranslated language.
-
C.
hasEnglishGloss
Indicates that one entity serves as the English-language gloss or explanatory translation for the other entity.
-
D.
originalLanguagePhrase
Indicates that one phrase is the original-language version from which another phrase (typically a translation or adaptation) is derived.
-
E.
languageOfOriginalDescription
chosen
Indicates that something is expressed or documented in its initial or source language version.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4f19708190a50f29598fb1a204 |
completed | April 29, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.