Triple
T31742382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangladesh–Pakistan relations |
E810175
|
entity |
| Predicate | hasEmbassyIn |
P12096
|
FINISHED |
| Object | Dhaka |
—
|
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: Dhaka | Statement: [Bangladesh–Pakistan relations, hasEmbassyIn, Dhaka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmbassyIn Context triple: [Bangladesh–Pakistan relations, hasEmbassyIn, Dhaka]
-
A.
hasConsulateOfUnitedStatesIn
Indicates that a consulate of the United States is located in the specified place.
-
B.
hasDiplomaticMission
chosen
Indicates that one entity maintains an official diplomatic representation, such as an embassy or mission, in the territory or jurisdiction of another entity.
-
C.
hasDiplomaticStaffFrom
Indicates that an entity has diplomatic personnel who originate from or represent another specified entity.
-
D.
haveEmbassyOfIndonesiaIn
Indicates that an entity hosts or contains an embassy representing Indonesia in a specified location.
-
E.
hasAmbassador
Indicates that one entity serves as an official diplomatic representative (ambassador) for 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_69f348e233cc819083b6695f70cd75d8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ab4a67348190b431329957c70213 |
completed | May 3, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:25 p.m.