Triple
T4004414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BGD |
E89489
|
entity |
| Predicate | associatedWithRegionOfCountry |
P12445
|
FINISHED |
| Object | South Asia |
—
|
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: South Asia | Statement: [BGD, associatedWithRegionOfCountry, South Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithRegionOfCountry Context triple: [BGD, associatedWithRegionOfCountry, South Asia]
-
A.
regionallyAssociatedWith
chosen
Indicates that two entities are connected or related based on sharing the same or overlapping geographic or regional context.
-
B.
associatedWithContinent
Indicates that an entity has a geographical or contextual connection to a specific continent.
-
C.
associatedWithNationality
Indicates that one entity has a connection or affiliation with the nationality of another entity.
-
D.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.