Triple
T10222750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khajauli |
E242621
|
entity |
| Predicate | borderingStateContext |
P88549
|
FINISHED |
| Object | near Nepal border |
—
|
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: near Nepal border | Statement: [Khajauli, borderingStateContext, near Nepal border]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingStateContext Context triple: [Khajauli, borderingStateContext, near Nepal border]
-
A.
borderStateOf
Indicates that one state shares a common boundary or border with another state.
-
B.
borderingCountryContext
Indicates that one country shares a land or maritime boundary with another within a specified geopolitical or temporal context.
-
C.
borderRiverContext
Indicates that a river serves as or is involved in forming the boundary between two geographic or political regions within a specific contextual setting.
-
D.
borderingStateOrProvince
chosen
Indicates that one state or province shares a common boundary with another state or province.
-
E.
borderingStateInfluence
Indicates that one state exerts political, economic, social, or security-related influence on another state with which it shares a land or maritime border.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa8305e481908ee1fc1d9eda6fa0 |
completed | April 6, 2026, 12:43 p.m. |
| PD | Predicate disambiguation | batch_69d3955f61f88190b8d37ff645cd44d3 |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:10 a.m.