Triple
T1231427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Kiel |
E26450
|
entity |
| Predicate | numberOfFaculties |
P24754
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [University of Kiel, numberOfFaculties, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFaculties Context triple: [University of Kiel, numberOfFaculties, 8]
-
A.
publicUniversityFaculty
Indicates that a person is a member of the faculty (e.g., professor, lecturer, instructor) at a public university.
-
B.
numberOfCampuses
Indicates the total count of campuses associated with a given entity.
-
C.
isLargestFacultyOf
Indicates that one faculty is the largest (typically by size, number of members, or resources) among all faculties within a given institution or context.
-
D.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
E.
numberOfColleges
Indicates the quantity of colleges associated with a given entity.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5a25348190a0665b6324c4d8f5 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bbf83584819088c69366f58586cc |
completed | March 1, 2026, 10:21 p.m. |
Created at: March 1, 2026, 7:47 p.m.