Triple
T25398198
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumding railway division |
E636347
|
entity |
| Predicate | hasNeighbouringDivision |
P168028
|
FINISHED |
| Object | Rangiya railway division |
—
|
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: Rangiya railway division | Statement: [Lumding railway division, hasNeighbouringDivision, Rangiya railway division]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbouringDivision Context triple: [Lumding railway division, hasNeighbouringDivision, Rangiya railway division]
-
A.
hasNeighborCensusDivision
Indicates that one census division is geographically adjacent to another census division.
-
B.
hasDivisionCounterpart
Indicates that one entity serves as the division-level equivalent or counterpart of another entity within an organizational or structural hierarchy.
-
C.
hasNeighbouringWard
Indicates that one ward is directly adjacent to or borders another ward geographically.
-
D.
hasBorderingSubdivision
Indicates that one subdivision directly borders or shares a boundary with another subdivision.
-
E.
hasNeighboringLGA
Indicates that one local government area is geographically adjacent to or directly borders another local government area.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 21, 2026, 1:50 p.m.