Triple
T27305828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myanmar–Bangladesh border |
E689052
|
entity |
| Predicate | associatedWithRefugeeCampArea |
P14231
|
FINISHED |
| Object | Cox’s Bazar Rohingya camps |
—
|
NE NERFINISHED |
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: Cox’s Bazar Rohingya camps | Statement: [Myanmar–Bangladesh border, associatedWithRefugeeCampArea, Cox’s Bazar Rohingya camps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithRefugeeCampArea Context triple: [Myanmar–Bangladesh border, associatedWithRefugeeCampArea, Cox’s Bazar Rohingya camps]
-
A.
nearRefugeeCamp
Indicates that one entity is located in close physical proximity to a refugee camp.
-
B.
hasRefugeeCamp
Indicates that a location or entity hosts, contains, or is the site of a refugee camp.
-
C.
locatedInRefugeeCamp
Indicates that an entity is situated within the boundaries of a refugee camp.
-
D.
majorResettlementArea
Indicates that a location serves as a primary or significant destination area where people are being resettled.
-
E.
associatedCamp
chosen
Indicates a relationship where an entity is linked or connected to a particular camp, typically as its relevant or affiliated camp.
- 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_69ef355b931c8190a63cafaf7bcc008b |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69ffe01c9d3c819084c256bb3c81c0dc |
completed | May 10, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69ffdfcc78b08190aa4493f13d62a531 |
completed | May 10, 2026, 1:30 a.m. |
Created at: April 27, 2026, 11:24 a.m.