Triple
T20603030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haparanda |
E506229
|
entity |
| Predicate | nearCurrencyBorderWith |
P140729
|
FINISHED |
| Object | euro area (Finland) |
—
|
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: euro area (Finland) | Statement: [Haparanda, nearCurrencyBorderWith, euro area (Finland)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearCurrencyBorderWith Context triple: [Haparanda, nearCurrencyBorderWith, euro area (Finland)]
-
A.
nearBorderBetween
Indicates that something is located close to the dividing line or boundary shared between two adjacent areas or regions.
-
B.
nearBorderDirection
Indicates that one entity is located close to a border or boundary in a specified directional orientation relative to that border.
-
C.
nearFormerBorderWith
Indicates that one entity is located close to where the former border or boundary with another entity used to be.
-
D.
nearBorderCrossing
Indicates that an entity is located close to a border crossing point between two regions or countries.
-
E.
borderStateNearby
Indicates that one state is geographically close to, but does not necessarily directly touch, the border of another state.
- F. None of above. chosen
Provenance (4 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_69e0b4bb2b4081908fa4a72444120f35 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa22663881909a8d4644e1c48dc2 |
completed | April 20, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69e59fffe1748190825e4eaa90340631 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a9f3f88190b961db9aca36f7da |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:41 a.m.