Triple
T26289510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belagavi Lok Sabha constituency |
E661226
|
entity |
| Predicate | borderStateInfluence |
P60546
|
FINISHED |
| Object | Maharashtra |
—
|
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: Maharashtra | Statement: [Belagavi Lok Sabha constituency, borderStateInfluence, Maharashtra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderStateInfluence Context triple: [Belagavi Lok Sabha constituency, borderStateInfluence, Maharashtra]
-
A.
borderingStateInfluence
chosen
Indicates that one state exerts political, economic, social, or security-related influence on another state with which it shares a land or maritime border.
-
B.
borderStateImplication
Indicates that a relationship or condition involving a border state logically leads to, or entails, another specific state or outcome.
-
C.
borderStateOf
Indicates that one state shares a common boundary or border with another state.
-
D.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
-
E.
borderStateOrigin
Indicates that a state shares a land or maritime border with the place where an entity originated.
- 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_69ee812bbd448190be4d7478b057990a |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 26, 2026, 10:07 p.m.