Triple
T29941280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kladno |
E760505
|
entity |
| Predicate | distanceToPrague_km |
P59333
|
FINISHED |
| Object | approximately 25 |
—
|
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 25 | Statement: [Kladno, distanceToPrague_km, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPrague_km Context triple: [Kladno, distanceToPrague_km, approximately 25]
-
A.
distanceFromPragueKmApprox
chosen
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
-
B.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
C.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
D.
distanceToOstrava
Indicates the measured or estimated distance between a given entity’s location and the city of Ostrava.
-
E.
distanceFromBrno
Indicates the spatial distance between a given entity and the city of Brno.
- 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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a00be8ee4bc8190b795d9606f0e490c |
completed | May 10, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_6a00bde163c88190867104bd08cac2ee |
completed | May 10, 2026, 5:18 p.m. |
Created at: April 29, 2026, 6:22 p.m.