Triple
T13441938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kraków Lotnisko railway station |
E320382
|
entity |
| Predicate | travelTimeToKrakówGłówny |
P109948
|
FINISHED |
| Object | approximately 17 minutes |
—
|
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 17 minutes | Statement: [Kraków Lotnisko railway station, travelTimeToKrakówGłówny, approximately 17 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeToKrakówGłówny Context triple: [Kraków Lotnisko railway station, travelTimeToKrakówGłówny, approximately 17 minutes]
-
A.
distanceToKraków_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Kraków.
-
B.
distanceToPoznań_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Poznań.
-
C.
distanceToKatowice
Indicates the spatial distance between a given entity and the city of Katowice.
-
D.
distanceToKielce
Indicates the spatial distance between a given entity and the city of Kielce.
-
E.
distanceToGdańsk_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Gdańsk.
- 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_69d80761e6cc8190a90c844589998ecc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaee704ac8190b4c7f4e0d3a88494 |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03ce03481908c61094f0cc0c158 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:40 p.m.