Triple
T7196849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ministry of Interior of Turkey |
E168635
|
entity |
| Predicate | hasCabinetMemberTitle |
P7410
|
FINISHED |
| Object | Minister of Interior of Turkey |
—
|
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: Minister of Interior of Turkey | Statement: [Ministry of Interior of Turkey, hasCabinetMemberTitle, Minister of Interior of Turkey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCabinetMemberTitle Context triple: [Ministry of Interior of Turkey, hasCabinetMemberTitle, Minister of Interior of Turkey]
-
A.
hasMinisterTitle
chosen
Indicates that an entity holds or is associated with a specific ministerial title or office.
-
B.
notableCabinetMember
Indicates that a person has served as a particularly prominent or significant member of a government cabinet.
-
C.
officeHolderTitle
Indicates the official position or title held by a person in an office or role.
-
D.
hasMinister
Indicates that one entity serves as the minister (political, religious, or administrative official) responsible for or associated with another entity.
-
E.
hasDeputyLeaderTitle
Indicates that an entity holds a specific title associated with the role of deputy leader.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e928ecdc8190a7f3feaf6d28781b |
completed | March 27, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:51 p.m.