Triple
T10784917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyushu University Medical Library |
E254426
|
entity |
| Predicate | hasStudySpace |
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: [Kyushu University Medical Library, hasStudySpace, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudySpace Context triple: [Kyushu University Medical Library, hasStudySpace, yes]
-
A.
offersStudySpaces
chosen
Indicates that one entity provides or makes available physical or virtual areas designated for studying to another entity.
-
B.
hasStudioSpaces
Indicates that an entity provides or contains one or more studio spaces for use (e.g., for work, production, or creative activities).
-
C.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
D.
hasLectureHall
Indicates that an entity possesses, includes, or is associated with a lecture hall as part of its facilities or structure.
-
E.
hasPublicSpaceAlong
Indicates that a public space (such as a park, plaza, or walkway) is located adjacent to or runs alongside the referenced feature or element.
- 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_69d6aa609f008190a294200aefcb7bd5 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d732d2e7cc8190a4cb9a4d7c76ab15 |
completed | April 9, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69d6f316940c819092a96c429629fdef |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.