Triple
T33032453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garissa County |
E845200
|
entity |
| Predicate | hasRefugeeComplex |
P30108
|
FINISHED |
| Object | Dadaab refugee complex |
E837607
|
NE 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: Dadaab refugee complex | Statement: [Garissa County, hasRefugeeComplex, Dadaab refugee complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRefugeeComplex Context triple: [Garissa County, hasRefugeeComplex, Dadaab refugee complex]
-
A.
hasRefugeePopulation
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
B.
hasRefugeeCamp
chosen
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
C.
wasRefugee
Indicates that an entity previously lived as a refugee, having been forced to leave their home country due to conflict, persecution, or disaster.
-
D.
hasNotableRefuge
Indicates that an entity is associated with a particularly important or well-known place of refuge or shelter.
-
E.
hasRefugeeMovements
Indicates that there are movements or flows of refugees involving the related entities, such as people fleeing from one place and arriving in another.
- F. None of above.
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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a033ed9322c8190be994a8d99761caa |
completed | May 12, 2026, 2:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34e50e5fb4819091f497eddf4a3244 |
completed | June 19, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_6a033df2b254819082a672859e5168e6 |
completed | May 12, 2026, 2:49 p.m. |
Created at: May 1, 2026, 1:24 a.m.