Triple
T72553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adelbert von Chamisso |
E1452
|
entity |
| Predicate | writingLanguage |
P2245
|
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: [Adelbert von Chamisso, writingLanguage, German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingLanguage Context triple: [Adelbert von Chamisso, writingLanguage, German]
-
A.
primaryLanguageOf
Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
-
B.
writingSystem
Indicates that one entity is the script or system of written symbols used to represent the language or content of another entity.
-
C.
draftedInLanguage
chosen
Indicates that a document, text, or content was originally written or composed using a specific natural language.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a252201fa481908e30791954119c17 |
completed | Feb. 28, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69a24eacfdc481909e9ff99752fd42bf |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.