Triple
T36436270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Černilov |
E897592
|
entity |
| Predicate | distanceToHradecKrálové |
P204872
|
FINISHED |
| Object | approximately 8–10 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 8–10 km | Statement: [Černilov, distanceToHradecKrálové, approximately 8–10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHradecKrálové Context triple: [Černilov, distanceToHradecKrálové, approximately 8–10 km]
-
A.
distanceToJihlava
Indicates the spatial distance between a given entity’s location and the city of Jihlava.
-
B.
distanceFromBrno
Indicates the spatial distance between a given entity and the city of Brno.
-
C.
distanceToBrno
Indicates the spatial distance between a given entity’s location and the city of Brno.
-
D.
distanceTo_ČeskéBudějovice
Indicates the spatial distance between a given entity and the location České Budějovice.
-
E.
distanceFromPragueKmApprox
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
- 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_69f76e56636481908eda808ab0273401 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:10 p.m.