Triple
T19467974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Equatoria region |
E487047
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Kapoeta
Kapoeta is a town in southeastern South Sudan that serves as an important local center for trade and administration in the Equatoria region.
|
E1377192
|
NE FINISHED |
How this triple was built (4 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: Kapoeta | Statement: [Equatoria region, hasMajorCity, Kapoeta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapoeta Context triple: [Equatoria region, hasMajorCity, Kapoeta]
-
A.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
-
B.
Sogakope
Sogakope is a town in southeastern Ghana known for its location along the lower Volta River and its role as a local commercial and transportation hub.
-
C.
Ténenkou
Ténenkou is a town and administrative center in central Mali, situated within the Mopti Region.
-
D.
Leipoa
Leipoa is a bird genus in the megapode family best known for including the Australian malleefowl, a ground-dwelling species that incubates its eggs in large mounds of decomposing vegetation.
-
E.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kapoeta Triple: [Equatoria region, hasMajorCity, Kapoeta]
Generated description
Kapoeta is a town in southeastern South Sudan that serves as an important local center for trade and administration in the Equatoria region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kapoeta Target entity description: Kapoeta is a town in southeastern South Sudan that serves as an important local center for trade and administration in the Equatoria region.
-
A.
Kabaena
Kabaena is an island in Indonesia known for its location off the coast of Sulawesi and its mix of coastal and hilly landscapes.
-
B.
Sogakope
Sogakope is a town in southeastern Ghana known for its location along the lower Volta River and its role as a local commercial and transportation hub.
-
C.
Ténenkou
Ténenkou is a town and administrative center in central Mali, situated within the Mopti Region.
-
D.
Leipoa
Leipoa is a bird genus in the megapode family best known for including the Australian malleefowl, a ground-dwelling species that incubates its eggs in large mounds of decomposing vegetation.
-
E.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
- F. None of above. chosen
Provenance (5 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e4b230819097c8804ee91988ea |
completed | April 20, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a073b40271c8190a27b00e6533ed1a0 |
completed | May 15, 2026, 3:26 p.m. |
| NEDg | Description generation | batch_6a073c19c3b88190a6114d272ebd5fbc |
completed | May 15, 2026, 3:30 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a073d25ba448190a62777b68d2f3136 |
completed | May 15, 2026, 3:35 p.m. |
Created at: April 10, 2026, 1:39 p.m.