Triple
T32328749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bukan |
E825987
|
entity |
| Predicate | borderingProvinceContext |
P88549
|
FINISHED |
| Object | near Kurdistan Province |
—
|
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 Kurdistan Province | Statement: [Bukan, borderingProvinceContext, near Kurdistan Province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderingProvinceContext Context triple: [Bukan, borderingProvinceContext, near Kurdistan Province]
-
A.
borderingCountryOfItsProvince
Indicates that one country shares a land border with the country to which a given province belongs.
-
B.
borderingCountryContext
Indicates that one country shares a land or maritime boundary with another within a specified geopolitical or temporal context.
-
C.
stateBorderContext
Indicates that one state shares a border with another state within a specified geographic or political context.
-
D.
borderingStateOrProvince
chosen
Indicates that one state or province shares a common boundary with another state or province.
-
E.
provinceBordering
Indicates that two provinces share a common boundary or border with each other.
- 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_69f34912d0c48190bba75770660320e9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fefb15220081908da36aac386fa582 |
completed | May 9, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69fefa8e8ad48190a723fed81e9d64d0 |
completed | May 9, 2026, 9:12 a.m. |
Created at: May 1, 2026, 12:47 a.m.