Triple
T1985879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Tartu Library |
E43138
|
entity |
| Predicate | hasSpecialCollections |
P35799
|
FINISHED |
| Object | Estonian studies |
—
|
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: Estonian studies | Statement: [University of Tartu Library, hasSpecialCollections, Estonian studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpecialCollections Context triple: [University of Tartu Library, hasSpecialCollections, Estonian studies]
-
A.
hasSpecials
Indicates that an entity offers or is associated with special deals, promotions, or limited-time offers.
-
B.
hasDigitalCollections
Indicates that an entity possesses or provides access to one or more collections of materials in digital form.
-
C.
hasSpecial
Indicates that an entity possesses or is associated with a distinctive or exceptional attribute, status, or feature compared to others.
-
D.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
-
E.
hasSpecialCategory
Indicates that an entity is associated with a designated special or exceptional category distinct from its standard classifications.
- 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.