Triple
T17655313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuřim |
E429606
|
entity |
| Predicate | locatedInDirectionFromBrno |
P128406
|
FINISHED |
| Object | northwest |
—
|
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: northwest | Statement: [Kuřim, locatedInDirectionFromBrno, northwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInDirectionFromBrno Context triple: [Kuřim, locatedInDirectionFromBrno, northwest]
-
A.
directionFromPrague
Indicates the cardinal or relative compass direction in which one entity is located from Prague.
-
B.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
C.
distanceFromPlzeň_km
Indicates the distance, measured in kilometers, between an entity and the city of Plzeň.
-
D.
distanceFromPragueKmApprox
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
-
E.
distanceTo_ČeskéBudějovice
Indicates the spatial distance between a given entity and the location České Budějovice.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e40e344819086a49c69f8f2956b |
completed | April 19, 2026, 5:55 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69e3cfaac2b881909e1140339eb1a0dd |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 6:06 a.m.