Triple
T36185462
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European route E85 |
E1046830
|
entity |
| Predicate | connectsSeaToSea |
P27556
|
FINISHED |
| Object | Baltic Sea to Aegean Sea |
—
|
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: Baltic Sea to Aegean Sea | Statement: [European route E85, connectsSeaToSea, Baltic Sea to Aegean Sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsSeaToSea Context triple: [European route E85, connectsSeaToSea, Baltic Sea to Aegean Sea]
-
A.
seaConnection
Indicates a relationship where two places are connected or accessible to each other via the sea, such as by maritime routes or coastal adjacency.
-
B.
hasSeaRouteConnection
chosen
Indicates that there exists a navigable maritime route linking two locations or entities.
-
C.
hasMaritimeConnection
Indicates a relationship in which an entity is linked to seas, oceans, or maritime activities, such as shipping, navigation, or coastal operations.
-
D.
connectsOcean
Indicates that one geographic entity serves as a link or passage between another entity and an ocean.
-
E.
associatedWithSeaRoute
Indicates a relationship where something is connected or related to a particular sea route, such as by use, location, or relevance.
- 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_69f76e3d4fbc81908c159c7beeb4ce00 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffa15d53208190ab8574d6c7913e18 |
completed | May 9, 2026, 9:04 p.m. |
| PD | Predicate disambiguation | batch_69ff9eee681c81909434e79c627cb528 |
completed | May 9, 2026, 8:54 p.m. |
Created at: May 3, 2026, 4:08 p.m.