Triple
T38033371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sweden–Finland border |
E948976
|
entity |
| Predicate | maritimeBorderLength |
P116153
|
FINISHED |
| Object | approximately 59 kilometres |
—
|
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: approximately 59 kilometres | Statement: [Sweden–Finland border, maritimeBorderLength, approximately 59 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritimeBorderLength Context triple: [Sweden–Finland border, maritimeBorderLength, approximately 59 kilometres]
-
A.
maritimeBoundaryLengthApproxKm
chosen
Indicates the approximate length, measured in kilometers, of a state's maritime boundary or coastline.
-
B.
totalLandBorderLength_km
Indicates the total length, in kilometers, of all land borders that an entity shares with neighboring entities.
-
C.
longestLandBorderWith
Indicates that two entities share a land border and that this border is the longest land border for at least one of the entities.
-
D.
hasCoastlineLengthRank
Indicates the relative position of an entity in an ordered ranking based on the length of its coastline.
-
E.
shareLandBorderLengthApproxKm
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.