Triple
T18463572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberbürgermeister |
E451098
|
entity |
| Predicate | literalTranslationToEnglish |
P31361
|
FINISHED |
| Object | supreme mayor |
—
|
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: supreme mayor | Statement: [Oberbürgermeister, literalTranslationToEnglish, supreme mayor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literalTranslationToEnglish Context triple: [Oberbürgermeister, literalTranslationToEnglish, supreme mayor]
-
A.
textTranslation
Indicates a relationship where one text is rendered into another language or form while preserving its original meaning.
-
B.
EnglishTranslation
chosen
Indicates that one expression is the English-language translation equivalent of another expression.
-
C.
translatedIn
Indicates that a work, text, or content has been rendered from its original language into another specified language or linguistic form.
-
D.
translationProperty
Indicates a relationship where one entity serves as a translated counterpart or translation-specific attribute of another entity.
-
E.
translationOn
Indicates that one entity is a translation of another entity, typically expressing the same content in a different language or linguistic form.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52a8190508190a74b1d3482364905 |
completed | April 19, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:33 a.m.