Triple
T7833563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brandýs nad Labem-Stará Boleslav |
E181632
|
entity |
| Predicate | distanceFromPrague_km |
P59333
|
FINISHED |
| Object | approximately 17 |
—
|
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 | Statement: [Brandýs nad Labem-Stará Boleslav, distanceFromPrague_km, approximately 17]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromPrague_km Context triple: [Brandýs nad Labem-Stará Boleslav, distanceFromPrague_km, approximately 17]
-
A.
distanceFromPragueKmApprox
chosen
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
-
B.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
C.
distanceToŽilina_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Žilina.
-
D.
distanceToPoznań_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Poznań.
-
E.
distanceToKraków_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Kraków.
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064a47648190af2ca2b336584a92 |
completed | March 30, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:45 p.m.