Triple
T7803413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Historical Museum |
E180486
|
entity |
| Predicate | hasLibraryHoldings |
P79099
|
FINISHED |
| Object | over 200,000 volumes |
—
|
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: over 200,000 volumes | Statement: [German Historical Museum, hasLibraryHoldings, over 200,000 volumes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLibraryHoldings Context triple: [German Historical Museum, hasLibraryHoldings, over 200,000 volumes]
-
A.
hasBorrowingSystem
Indicates that an entity possesses or employs a system or mechanism for borrowing items, resources, or services.
-
B.
hasDigitalLibrary
Indicates that an entity maintains or provides access to a collection of digital resources or publications.
-
C.
hasCirculationFeature
Indicates that an entity possesses a specific feature related to movement or flow within a system, such as circulation paths, routes, or mechanisms.
-
D.
hasDigitalLibraryServices
Indicates that an entity provides or supports access to digital library-related services or resources.
-
E.
libraryStatus
Indicates the current availability or circulation state of an item within a library system (e.g., available, checked out, on hold).
- F. None of above. chosen
Provenance (4 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:34 p.m.