Triple
T10899303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzania and Burundi |
E257394
|
entity |
| Predicate | haveRefugeeMovementsBetween |
P94592
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Tanzania and Burundi, haveRefugeeMovementsBetween, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveRefugeeMovementsBetween Context triple: [Tanzania and Burundi, haveRefugeeMovementsBetween, yes]
-
A.
hasRefugeeMovements
chosen
Indicates that there are movements or flows of refugees involving the related entities, such as people fleeing from one place and arriving in another.
-
B.
historicalPopulationMovement
Indicates the movement or migration of a population from one place to another during a specific historical period or event.
-
C.
hasRefugeeCamp
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
D.
hasSignificantEmigrationTo
Indicates that a substantial number of people leave one place, group, or entity to move and settle in another specific place, group, or entity.
-
E.
hasRefugeePopulation
Indicates that an entity hosts, contains, or is associated with a population of refugees.
- F. None of above.
Provenance (3 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_69d6aa8550c8819095508a2ed9acf3db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d761a2392c8190bc2c2359d63eff7a |
completed | April 9, 2026, 8:21 a.m. |
| PD | Predicate disambiguation | batch_69d70d3d69e08190bb369e9a7927142c |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:21 p.m.