Triple
T11775189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Service flag of Germany |
E279999
|
entity |
| Predicate | languageLabel_de |
P22792
|
FINISHED |
| Object | Dienstflagge der Bundesbehörden |
—
|
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: Dienstflagge der Bundesbehörden | Statement: [Service flag of Germany, languageLabel_de, Dienstflagge der Bundesbehörden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageLabel_de Context triple: [Service flag of Germany, languageLabel_de, Dienstflagge der Bundesbehörden]
-
A.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
-
B.
nameInGerman
chosen
Indicates that an entity is known or referred to by a specific name in the German language.
-
C.
containsGermanSpeakingArea
Indicates that one entity geographically includes an area where German is predominantly spoken.
-
D.
languageOnAustrianSide
Indicates that a particular language is used or present on the Austrian side of a border, context, or interaction.
-
E.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
- 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_69d6ab01d2688190ad8ed6bda487eaa5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a8c2e8b08190a31b1e284fca2aee |
completed | April 10, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69d8a242cd8c819086ed6c5f292dc8cb |
completed | April 10, 2026, 7:09 a.m. |
Created at: April 8, 2026, 9:41 p.m.