Triple
T32597955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kysucké Nové Mesto |
E833274
|
entity |
| Predicate | distanceToŽilina |
P43823
|
FINISHED |
| Object | approximately 10 km to the north |
—
|
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 10 km to the north | Statement: [Kysucké Nové Mesto, distanceToŽilina, approximately 10 km to the north]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToŽilina Context triple: [Kysucké Nové Mesto, distanceToŽilina, approximately 10 km to the north]
-
A.
distanceToŽilina_km
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Žilina.
-
B.
distanceToJihlava
Indicates the spatial distance between a given entity’s location and the city of Jihlava.
-
C.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
D.
distanceFromBrno
Indicates the spatial distance between a given entity and the city of Brno.
-
E.
distanceToOstrava
Indicates the measured or estimated distance between a given entity’s location and the city of Ostrava.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:05 a.m.