Triple
T29379825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minister of Agriculture, Animal Industry and Fisheries |
E745103
|
entity |
| Predicate | positionInceptionCountry |
P194657
|
FINISHED |
| Object | Uganda |
—
|
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: Uganda | Statement: [Minister of Agriculture, Animal Industry and Fisheries, positionInceptionCountry, Uganda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInceptionCountry Context triple: [Minister of Agriculture, Animal Industry and Fisheries, positionInceptionCountry, Uganda]
-
A.
ownerCountry
Indicates the country that has legal ownership or control over a given entity.
-
B.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
C.
projectCountryAtTheTime
Indicates the country with which a project was associated at the specific time or period in question.
-
D.
acquisitionCountry
Indicates the country in which the acquisition of an entity or asset took place.
-
E.
locationCountryAtTheTime
Indicates that an entity was located in a specified country during a particular time or time period.
- 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_69f0a79cfd5481909b4dde750cb8d2c6 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd7fdafbe881908a31fcb407af2c34 |
completed | May 8, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69fd7ef0ea908190b5d83f71565bdb1c |
completed | May 8, 2026, 6:13 a.m. |
| PDg | Predicate description generation | batch_69fd7fd9be2881908a7f00e0e8822de8 |
completed | May 8, 2026, 6:16 a.m. |
Created at: April 28, 2026, 2:34 p.m.