Triple
T2495374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghan–Pakistan relations |
E52141
|
entity |
| Predicate | refugeeDimension |
P9069
|
FINISHED |
| Object | Afghan refugees in Pakistan |
—
|
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: Afghan refugees in Pakistan | Statement: [Afghan–Pakistan relations, refugeeDimension, Afghan refugees in Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refugeeDimension Context triple: [Afghan–Pakistan relations, refugeeDimension, Afghan refugees in Pakistan]
-
A.
hasRefugeePopulation
chosen
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
B.
displacedPeopleEstimate
Indicates an estimated number of people who have been forced to leave their homes or usual places of residence due to a particular event or situation.
-
C.
hasRefugeeCamp
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
D.
approximateNumberOfRefugeesTransported
Indicates an estimated count of refugees who were transported in the described event or context.
-
E.
countryOfAsylum
Indicates that one entity serves as the country providing asylum or refuge to another entity.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd19541048190b9e39db119c20fe8 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.