Triple
T21394516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamu County |
E527743
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Mpeketoni
Mpeketoni is a small agricultural and trading town in coastal Kenya known for its predominantly farming community and proximity to Lamu Island.
|
E1482620
|
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: Mpeketoni | Statement: [Lamu County, hasSettlement, Mpeketoni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mpeketoni Context triple: [Lamu County, hasSettlement, Mpeketoni]
-
A.
Kapoeta
Kapoeta is a town in southeastern South Sudan that serves as an important local center for trade and administration in the Equatoria region.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Matupi
Matupi is a remote town in Myanmar's Chin State, known as a gateway to the mountainous region that includes Nat Ma Taung (Mount Victoria).
-
D.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
-
E.
Mekoche
Mekoche is one of the principal divisions of the Shawnee people, historically recognized as a distinct clan or band within the larger Shawnee nation.
- 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: Mpeketoni Triple: [Lamu County, hasSettlement, Mpeketoni]
Generated description
Mpeketoni is a small agricultural and trading town in coastal Kenya known for its predominantly farming community and proximity to Lamu Island.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mpeketoni Target entity description: Mpeketoni is a small agricultural and trading town in coastal Kenya known for its predominantly farming community and proximity to Lamu Island.
-
A.
Kapoeta
Kapoeta is a town in southeastern South Sudan that serves as an important local center for trade and administration in the Equatoria region.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Matupi
Matupi is a remote town in Myanmar's Chin State, known as a gateway to the mountainous region that includes Nat Ma Taung (Mount Victoria).
-
D.
Mungaka
Mungaka is a Grassfields Bantu language spoken primarily in Cameroon, particularly associated with the Bamunka (Ndop) area.
-
E.
Mekoche
Mekoche is one of the principal divisions of the Shawnee people, historically recognized as a distinct clan or band within the larger Shawnee nation.
- 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_69e0b51ff3748190935c0a513c62a12b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b117d8c881908b823c1212b5b919 |
completed | April 22, 2026, 11:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09bb4a9390819093f0ce34f96420ce |
completed | May 17, 2026, 12:57 p.m. |
| NEDg | Description generation | batch_6a09bea3994481908b7a782fd384603a |
completed | May 17, 2026, 1:12 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09bf9d2d508190a45847afa0d47337 |
completed | May 17, 2026, 1:16 p.m. |
Created at: April 16, 2026, 5:13 p.m.