Triple
T35311663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Von Abtuhung der Bylder |
E1019787
|
entity |
| Predicate | hasTitleInModernGermanOrthography |
P6492
|
FINISHED |
| Object | Von Abtuhung der Bilder |
—
|
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: Von Abtuhung der Bilder | Statement: [Von Abtuhung der Bylder, hasTitleInModernGermanOrthography, Von Abtuhung der Bilder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInModernGermanOrthography Context triple: [Von Abtuhung der Bylder, hasTitleInModernGermanOrthography, Von Abtuhung der Bilder]
-
A.
hasTitleInGerman
chosen
Indicates that an entity has a specific title or name expressed in the German language.
-
B.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
-
C.
hasTitleInModernEnglish
Indicates that an entity is associated with a specific title expressed in modern English.
-
D.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
E.
hasTitleInRevisedRomanization
Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
- 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_69f76de8b4c48190ae504b86185c474c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fdd2be648c8190b60b3d1caeb44364 |
completed | May 8, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69fdd14a5c708190a6f95ec61f4fc28f |
completed | May 8, 2026, 12:04 p.m. |
Created at: May 3, 2026, 4:03 p.m.