Triple
T1985862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Tartu Library |
E43138
|
entity |
| Predicate | offersInterlibraryLoan |
P35797
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [University of Tartu Library, offersInterlibraryLoan, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersInterlibraryLoan Context triple: [University of Tartu Library, offersInterlibraryLoan, yes]
-
A.
sharesLibrariesWith
Indicates that two entities use or depend on at least one of the same libraries or library components.
-
B.
library
Indicates that an entity functions as or is associated with a library, typically as a place or system for storing, organizing, and providing access to collections of information resources.
-
C.
memberInstitutionsOffer
Indicates that the member institutions provide or make available a particular service, program, or resource.
-
D.
librarySystem
Indicates a relationship where an organized framework or infrastructure manages, catalogs, and provides access to library resources and services.
-
E.
libraryCollectionFocus
Indicates that a library’s collection is primarily oriented toward or specialized in a particular subject, audience, or type of material.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69abb96e07c08190beed60096e9d71b4 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:37 p.m.