Triple
T25708600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deutsche Grenzpolizei |
E644667
|
entity |
| Predicate | operatedOnBorderWith |
P32580
|
FINISHED |
| Object | Federal Republic of Germany |
—
|
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: Federal Republic of Germany | Statement: [Deutsche Grenzpolizei, operatedOnBorderWith, Federal Republic of Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedOnBorderWith Context triple: [Deutsche Grenzpolizei, operatedOnBorderWith, Federal Republic of Germany]
-
A.
operatesOnBorderWith
chosen
Indicates that one entity conducts activities or exerts influence along or across the shared border it has with another entity.
-
B.
borderedBy
Indicates that one entity shares a common boundary or edge with another entity.
-
C.
connectsToCountryBorder
Indicates that one entity is directly adjacent to and touches the border of a specified country.
-
D.
crossesBorderOf
Indicates that one entity passes from one side of the boundary of another entity (typically a region or area) to the other side, traversing its border.
-
E.
borderingCountryOnOtherSide
Indicates that one country lies on the opposite side of a shared border relative to another 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 21, 2026, 9:08 p.m.