Triple
T20815677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapolca |
E512430
|
entity |
| Predicate | distanceFromLakeBalaton |
P141934
|
FINISHED |
| Object | approximately 12 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 12 km | Statement: [Tapolca, distanceFromLakeBalaton, approximately 12 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLakeBalaton Context triple: [Tapolca, distanceFromLakeBalaton, approximately 12 km]
-
A.
distanceToKecskemét_km
Indicates the physical distance, measured in kilometers, from a given location to Kecskemét.
-
B.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
-
C.
distanceToSzeged_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Szeged.
-
D.
distanceToBega_km
Indicates the physical distance, measured in kilometers, between a given location and Bega.
-
E.
distanceFromBratislava_km
Indicates the distance, measured in kilometers, between a given entity’s location and the city of Bratislava.
- 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_69e0b4cd25088190b48ca9700cd24efc |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2d5a514819093d1a18626de8857 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:41 p.m.