Triple
T7488822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish–German border |
E176949
|
entity |
| Predicate | hasDemarcationMethod |
P3951
|
FINISHED |
| Object | border markers and boundary stones |
—
|
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: border markers and boundary stones | Statement: [Danish–German border, hasDemarcationMethod, border markers and boundary stones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDemarcationMethod Context triple: [Danish–German border, hasDemarcationMethod, border markers and boundary stones]
-
A.
demarcationType
chosen
Indicates the specific way in which a boundary or separation between entities is defined, marked, or categorized.
-
B.
demarcationStatus
Indicates the current state or condition of how clearly and officially a boundary or division between entities is defined or marked.
-
C.
separationMethod
Indicates the technique or process used to separate one substance, component, or entity from another.
-
D.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
-
E.
hasObservationMethod
Indicates that a particular method, technique, or procedure is used to perform or obtain an observation.
- 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_69c69f24ac508190bb98fe927c0bd065 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f55abcd481909e42ca857fe46cd1 |
completed | March 27, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69c6f03eeaa88190a5215772ed05ee9f |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:43 p.m.