Triple
T13579181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faculty of Letters, Ankara University |
E324365
|
entity |
| Predicate | hasAcademicStaffIn |
P47
|
FINISHED |
| Object | language 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: language studies | Statement: [Faculty of Letters, Ankara University, hasAcademicStaffIn, language studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAcademicStaffIn Context triple: [Faculty of Letters, Ankara University, hasAcademicStaffIn, language studies]
-
A.
hasAcademicStaff
chosen
Indicates that an institution or organization employs or is associated with one or more academic staff members.
-
B.
hasFacultyIn
Indicates that an institution or organization has faculty members associated with or working in a particular department, field, or academic unit.
-
C.
hasFaculty
Indicates that an institution or department possesses or is associated with one or more faculty members.
-
D.
hasAcademicDepartment
Indicates that an institution or organization includes or is associated with a specific academic department.
-
E.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb03052088190a2b68c106059828e |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:48 p.m.