Triple
T10489517
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chad–Sudan border |
E247377
|
entity |
| Predicate | hasRefugeeMovements |
P94592
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Chad–Sudan border, hasRefugeeMovements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRefugeeMovements Context triple: [Chad–Sudan border, hasRefugeeMovements, true]
-
A.
hasRefugeePopulation
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
B.
hasRefugeeCamp
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.
approximateNumberOfRefugeesTransported
Indicates an estimated count of refugees who were transported in the described event or context.
-
E.
hasNotableRefuge
Indicates that an entity is associated with a particularly important or well-known place of refuge or shelter.
- F. None of above. chosen
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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097ca5c081908b47a08ca7885650 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d5092af880819082b42c0a68e45c5f |
completed | April 7, 2026, 1:39 p.m. |
Created at: April 6, 2026, 12:23 p.m.