Triple
T36622126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kazakhstan–Kyrgyzstan border |
E904070
|
entity |
| Predicate | hasBorderCountryOnSide |
P40061
|
FINISHED |
| Object | Kazakhstan |
—
|
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: Kazakhstan | Statement: [Kazakhstan–Kyrgyzstan border, hasBorderCountryOnSide, Kazakhstan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderCountryOnSide Context triple: [Kazakhstan–Kyrgyzstan border, hasBorderCountryOnSide, Kazakhstan]
-
A.
hasBorderWithinCountry
Indicates that one region or area shares an internal boundary with another region or area within the same country.
-
B.
hasBorderWithNonSovereignEntity
Indicates that one entity shares a land or maritime border with a political or territorial unit that is not fully sovereign.
-
C.
borderCountrySide
Indicates that one country shares a land border with the side or region of another country.
-
D.
hasBorderMeetingCountry
chosen
Indicates that one country shares a land or maritime border with another country.
-
E.
connectsToCountryBorder
Indicates that one entity is directly adjacent to and touches the border of a specified 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_69f76e6ae750819096911e6e2d4d12c5 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fe349879848190bcd77e3cc3470458 |
completed | May 8, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69fe31e3cf908190b23ebc2f7fe58722 |
completed | May 8, 2026, 6:56 p.m. |
Created at: May 3, 2026, 4:11 p.m.