Triple
T31961662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyborg Municipality |
E816056
|
entity |
| Predicate | bordersAcrossWater |
P19612
|
FINISHED |
| Object | Slagelse Municipality |
—
|
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: Slagelse Municipality | Statement: [Nyborg Municipality, bordersAcrossWater, Slagelse Municipality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bordersAcrossWater Context triple: [Nyborg Municipality, bordersAcrossWater, Slagelse Municipality]
-
A.
bordersStateAcrossSea
Indicates that one state is separated from another by a sea but still directly borders it across that body of water.
-
B.
borderingWaters
Indicates that a geographic area directly touches or is adjacent to a particular body of water.
-
C.
bordersCountryViaWaterway
Indicates that two countries share a boundary that is defined or connected by a waterway such as a river, canal, or strait.
-
D.
bordersCountyAcrossWater
chosen
Indicates that one county is separated from and adjacent to another county by a body of water rather than by land.
-
E.
sharesMaritimeBorders
Indicates that two entities have adjacent territorial waters or maritime zones that touch or overlap, forming a shared sea boundary.
- 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fedfd913f48190bdcd450980868d9a |
completed | May 9, 2026, 7:18 a.m. |
| PD | Predicate disambiguation | batch_69fedf58c6e88190821a7156054c9086 |
completed | May 9, 2026, 7:16 a.m. |
Created at: May 1, 2026, 12:09 a.m.