Triple
T22401084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libya–Tunisia border |
E553759
|
entity |
| Predicate | hasRefugeeFlows |
P94592
|
FINISHED |
| Object | Libyan refugees into Tunisia |
—
|
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: Libyan refugees into Tunisia | Statement: [Libya–Tunisia border, hasRefugeeFlows, Libyan refugees into Tunisia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRefugeeFlows Context triple: [Libya–Tunisia border, hasRefugeeFlows, Libyan refugees into Tunisia]
-
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.
hasRefugeePopulation
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
C.
hasRefugeeCamp
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
D.
wasRefugee
Indicates that an entity previously lived as a refugee, having been forced to leave their home country due to conflict, persecution, or disaster.
-
E.
refugeeAdministration
Indicates the management, coordination, or oversight of services, policies, and procedures related to 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_69e11e4da7048190b4387d422a9a0de5 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158b39c908190a735aa860d733869 |
completed | April 29, 2026, 1:02 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
Created at: April 16, 2026, 8:46 p.m.