Triple
T35149290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sânnicolau Mare |
E1014939
|
entity |
| Predicate | distanceToHungarianBorder |
P206852
|
FINISHED |
| Object | approximately 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 10 km | Statement: [Sânnicolau Mare, distanceToHungarianBorder, approximately 10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHungarianBorder Context triple: [Sânnicolau Mare, distanceToHungarianBorder, approximately 10 km]
-
A.
distanceToAustrianBorder
Indicates the measured spatial distance between a given entity’s location and the border of Austria.
-
B.
distanceToPolishBorder
Indicates the measured distance between a given location and the nearest point on the border of Poland.
-
C.
distanceToBulgarianBorder_km
Indicates the distance, measured in kilometers, from a given location to the nearest point on the Bulgarian national border.
-
D.
borderLengthWithHungary_km
Indicates the length, in kilometers, of the border that an entity shares with Hungary.
-
E.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:02 p.m.