Triple
T11969780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lębork |
E284885
|
entity |
| Predicate | distanceToBalticCoast |
P15760
|
FINISHED |
| Object | approximately 30 km |
—
|
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 30 km | Statement: [Lębork, distanceToBalticCoast, approximately 30 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBalticCoast Context triple: [Lębork, distanceToBalticCoast, approximately 30 km]
-
A.
distanceToBlackSea
Indicates the measured spatial distance between a given entity and the Black Sea.
-
B.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
C.
distanceToKiel_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Kiel.
-
D.
distanceFromCoast
chosen
Indicates the measured spatial separation between a location and the nearest point on a coastline.
-
E.
distanceFromTallinn
Indicates the measured distance between a given place or object and the city of Tallinn.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037bee54819085242a3ef3e286f9 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.