Triple
T23972353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siliguri Corridor |
E604268
|
entity |
| Predicate | nearInternationalBorderSegment |
P46305
|
FINISHED |
| Object | India–Bangladesh border |
—
|
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: India–Bangladesh border | Statement: [Siliguri Corridor, nearInternationalBorderSegment, India–Bangladesh border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearInternationalBorderSegment Context triple: [Siliguri Corridor, nearInternationalBorderSegment, India–Bangladesh border]
-
A.
nearInternationalBoundary
chosen
Indicates that one entity is located close to an international boundary separating two or more countries.
-
B.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
C.
nearBorderCrossing
Indicates that an entity is located close to a border crossing point between two regions or countries.
-
D.
nearStateBorderWith
Indicates that one entity is located close to the state border shared with another specified state or region.
-
E.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
- 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_69e29543019c8190872462e593cc50b4 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d1dcef248190a04718f6f436dcc8 |
completed | April 29, 2026, 9:39 a.m. |
| PD | Predicate disambiguation | batch_69f161578d54819084a8b35496299993 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:25 p.m.