Triple
T12442993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghanistan and Pakistan |
E297321
|
entity |
| Predicate | refugeeContext |
P9069
|
FINISHED |
| Object | large Afghan refugee population 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: large Afghan refugee population in Pakistan | Statement: [Afghanistan and Pakistan, refugeeContext, large Afghan refugee population in Pakistan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refugeeContext Context triple: [Afghanistan and Pakistan, refugeeContext, large Afghan refugee population in Pakistan]
-
A.
wasRefugee
Indicates that an entity previously lived as a refugee, having been forced to leave their home country due to conflict, persecution, or disaster.
-
B.
refugeeAdministration
Indicates the management, coordination, or oversight of services, policies, and procedures related to refugees.
-
C.
primaryRefugeeGroup
Indicates that the referenced group is the main or principal group of refugees associated with a particular context, event, or record.
-
D.
hasRefugeeCamp
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
E.
hasRefugeePopulation
chosen
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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95151e7348190a1d4953a8b416a13 |
completed | April 10, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69d94d3c27a08190a0237200203e476d |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.