Triple
T29301658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | President of the Republic of Mahabad |
E742975
|
entity |
| Predicate | countryOfCitizenshipOfOfficeHolders |
P17302
|
FINISHED |
| Object | Republic of Mahabad |
—
|
NE NERFINISHED |
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: Republic of Mahabad | Statement: [President of the Republic of Mahabad, countryOfCitizenshipOfOfficeHolders, Republic of Mahabad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryOfCitizenshipOfOfficeHolders Context triple: [President of the Republic of Mahabad, countryOfCitizenshipOfOfficeHolders, Republic of Mahabad]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
officeHolderNationality
chosen
Indicates that the nationality of an office holder is a specified country or nation.
-
C.
creatorCountryOfCitizenship
Indicates the country in which the creator holds or held legal citizenship.
-
D.
countryOfNobility
Indicates the country from which a person's noble title or status originates or is held.
-
E.
possibleCountryOfCitizenship
Indicates that an entity could plausibly be a country in which the person or agent may hold, or be eligible to hold, citizenship.
- 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_69f09123ed9881909f351f7541933f5e |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
Created at: April 28, 2026, 1:10 p.m.