Triple
T1522266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karen people |
E32254
|
entity |
| Predicate | refugeeStatus |
P9069
|
FINISHED |
| Object | protracted refugee population in Thailand |
—
|
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: protracted refugee population in Thailand | Statement: [Karen people, refugeeStatus, protracted refugee population in Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refugeeStatus Context triple: [Karen people, refugeeStatus, protracted refugee population in Thailand]
-
A.
hasRefugeePopulation
chosen
Indicates that an entity hosts, contains, or is associated with a population of refugees.
-
B.
receivedAsylumFrom
Indicates that one entity was granted asylum or refuge by another entity, typically a state or institution.
-
C.
attemptedToSeekAsylumIn
Indicates that an entity tried, but may not have succeeded, to obtain asylum in a particular place or country.
-
D.
yearOfAsylum
Indicates the specific year in which an entity was granted or obtained asylum.
-
E.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93d4756888190bf3872154de11539 |
completed | March 5, 2026, 8:22 a.m. |
| PD | Predicate disambiguation | batch_69a907ac7ea081908dd95bb5cc3b9847 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.