Triple
T25439434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baduria |
E637460
|
entity |
| Predicate | hasBorderAreaCharacteristics |
P160921
|
FINISHED |
| Object | cross-border trade influence |
—
|
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: cross-border trade influence | Statement: [Baduria, hasBorderAreaCharacteristics, cross-border trade influence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderAreaCharacteristics Context triple: [Baduria, hasBorderAreaCharacteristics, cross-border trade influence]
-
A.
hasBorderAreaStatus
Indicates that an entity has a designated status related to being in or associated with a border area.
-
B.
hasBorderLengthCharacteristic
Indicates that a border is associated with a specific length-related property or characteristic.
-
C.
hasBorderCode
Indicates that there is an associated code or identifier specifying the type or status of a border between entities.
-
D.
hasBorderThrough
Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
-
E.
hadBorderType
Indicates that a boundary between two entities existed and specifies the nature or classification of that border (e.g., land, maritime, disputed).
- F. None of above. chosen
Provenance (4 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f60cd7b3e88190a1206958c0f0b225 |
completed | May 2, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f60c32ce088190a620eb59d2499fa9 |
completed | May 2, 2026, 2:37 p.m. |
Created at: April 21, 2026, 2 p.m.