Triple
T9941860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opava |
E194100
|
entity |
| Predicate | distanceToOstrava |
P91270
|
FINISHED |
| Object | approximately 30 kilometres |
—
|
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 30 kilometres | Statement: [Opava, distanceToOstrava, approximately 30 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToOstrava Context triple: [Opava, distanceToOstrava, approximately 30 kilometres]
-
A.
distanceToŽilina_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Žilina.
-
B.
distanceToOstróda
Indicates the spatial distance between a given entity or location and the town of Ostróda.
-
C.
distanceFromPragueKmApprox
Indicates an approximate distance, measured in kilometers, between a given entity and the city of Prague.
-
D.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
-
E.
distanceToKatowice
Indicates the spatial distance between a given entity and the city of Katowice.
- 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_69ca82e409348190a393777356b80a2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb610905c81909d669265c92021a5 |
completed | April 2, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:44 p.m.