Triple
T1985864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Tartu Library |
E43138
|
entity |
| Predicate | offersStudySpaces |
P35798
|
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, offersStudySpaces, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersStudySpaces Context triple: [University of Tartu Library, offersStudySpaces, yes]
-
A.
campusUse
Indicates that something is intended for, associated with, or occurring in the use or activities of a campus or campus community.
-
B.
campusArea
Indicates that one entity is the physical area or spatial extent of a campus associated with another entity.
-
C.
hasNearbyInstitution
Indicates that one entity is located close to or in the immediate vicinity of an institution.
-
D.
campusFacilityType
Indicates the specific kind of facility a campus location is classified as (e.g., library, laboratory, residence hall).
-
E.
otherSeat
Indicates that one entity is the alternative or different seat relative to another seat in a given context.
- 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.