Triple
T4855634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France and Switzerland |
E108530
|
entity |
| Predicate | shareLandBorder |
P30010
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [France and Switzerland, shareLandBorder, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLandBorder Context triple: [France and Switzerland, shareLandBorder, yes]
-
A.
shareLandBorderRegion
Indicates that two regions are adjacent such that their land areas directly touch along a common boundary.
-
B.
shareLandBorderLengthApproxKm
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
-
C.
countryBordering
Indicates that one country shares a land or maritime boundary directly with another country.
-
D.
sharesInternationalBorderWith
chosen
Indicates that two geographic or political entities have a common boundary that is recognized as an international border.
-
E.
countryBorderFeatureOf
Indicates that a geographical feature (such as a river, mountain range, or coastline) serves as or is part of the border of a 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_69bd440a89548190a5f14ba6da6b97dc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2557388190a2d15571bacd24f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.