Triple
T23167892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greater Upper Nile |
E578761
|
entity |
| Predicate | containsAdministrativeArea |
P747
|
FINISHED |
| Object | Unity State |
—
|
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: Unity State | Statement: [Greater Upper Nile, containsAdministrativeArea, Unity State]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Unity State Context triple: [Greater Upper Nile, containsAdministrativeArea, Unity State]
-
A.
Unity State
chosen
Unity State is an oil-rich region in northern South Sudan that became a major battleground and humanitarian crisis zone during the South Sudanese Civil War.
-
B.
ConcreteState
ConcreteState is a specific implementation of the State interface in the State design pattern that encapsulates behavior associated with a particular state of a context object.
-
C.
FSM
FSM is the abbreviation for the French Submarine Forces, the branch of the French Navy responsible for operating and maintaining France’s submarine fleet, including its nuclear deterrent.
-
D.
FSM
FSM is the three-letter ISO 3166-1 alpha-3 country code for the Federated States of Micronesia, a Pacific island nation.
-
E.
Stateflow
Stateflow is a MATLAB tool for designing and simulating state machines and control logic, often used alongside Simulink for modeling complex event-driven systems.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f2d51288190af0d5747090d8e5d |
completed | April 29, 2026, 4:55 a.m. |
Created at: April 17, 2026, 4:03 p.m.