Triple
T32000192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Districts of Bavaria |
E817103
|
entity |
| Predicate | hasOfficialTermInGerman |
P156066
|
FINISHED |
| Object | Landkreise in Bayern |
—
|
NE NERFINISHED |
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: Landkreise in Bayern | Statement: [Districts of Bavaria, hasOfficialTermInGerman, Landkreise in Bayern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialTermInGerman Context triple: [Districts of Bavaria, hasOfficialTermInGerman, Landkreise in Bayern]
-
A.
hasOfficialLanguageNameInGerman
chosen
Indicates that an entity has an official language name expressed specifically in the German language.
-
B.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
-
C.
correspondsToAbbreviationInGerman
Indicates that one entity is the full form or concept for which the other entity serves as the corresponding abbreviation in the German language.
-
D.
officialTermLanguage
Indicates the language in which an official term is formally expressed or defined.
-
E.
hasOfficialShortNameInEnglish
Indicates that an entity has a designated official short form of its name expressed in English.
- 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_69f348f8ce388190ae84376b1f348f12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: May 1, 2026, 12:14 a.m.