Triple
T24615318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haiming, Germany |
E609238
|
entity |
| Predicate | hasBorderNearby |
P144886
|
FINISHED |
| Object | Austria |
—
|
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: Austria | Statement: [Haiming, Germany, hasBorderNearby, Austria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBorderNearby Context triple: [Haiming, Germany, hasBorderNearby, Austria]
-
A.
hasBorderThrough
Indicates that a border between two regions or entities passes through or along a specified intermediate area, feature, or object.
-
B.
hasNearbyBoundary
Indicates that one entity’s boundary lies close to, but does not necessarily touch or coincide with, the boundary of another entity.
-
C.
hasBorderConnection
Indicates that two regions or entities share a common boundary or are directly connected along a border.
-
D.
nearStateBorderWith
chosen
Indicates that one entity is located close to the state border shared with another specified state or region.
-
E.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
- 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_69e2c4d1140081909c58667bf68f80c3 |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:31 a.m.