Triple
T33830708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gambela Peoples’ Regional State |
E867089
|
entity |
| Predicate | borderTypeWithSouthSudan |
P199580
|
FINISHED |
| Object | international land border |
—
|
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: international land border | Statement: [Gambela Peoples’ Regional State, borderTypeWithSouthSudan, international land border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTypeWithSouthSudan Context triple: [Gambela Peoples’ Regional State, borderTypeWithSouthSudan, international land border]
-
A.
borderTypeWithSouthAfrica
Indicates the type or nature of the border that an entity shares with South Africa.
-
B.
borderTypeWithMongolia
Indicates the specific nature or classification of the border that an entity shares with Mongolia.
-
C.
borderTypeWithYemen
Indicates the type or nature of the border that exists between a given entity and Yemen.
-
D.
borderTypeWithJordan
Indicates the type or nature of the border that an entity shares with Jordan.
-
E.
borderTypeWithKenya
Indicates the type or nature of the border relationship that an entity shares with Kenya.
- 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_69f34991dd248190a659541588506b3c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff46afe7e481908f2862ed11c88db2 |
completed | May 9, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69ff45e9151881909c444a655e852165 |
completed | May 9, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69ff46aefe248190a80d898df6ef1340 |
completed | May 9, 2026, 2:37 p.m. |
Created at: May 1, 2026, 1:46 a.m.