Triple
T15330951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kupa |
E366528
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Delnice |
E313749
|
NE 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: Delnice | Statement: [Kupa, flowsNear, Delnice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delnice Context triple: [Kupa, flowsNear, Delnice]
-
A.
Delnice
chosen
Delnice is a small town in western Croatia known as a mountain and winter sports center in the Gorski Kotar region.
-
B.
Kavečany
Kavečany is a borough of Košice in eastern Slovakia, known for its hilly landscape, recreational areas, and proximity to major attractions like the Košice Zoo and ski facilities.
-
C.
Krhanice
Krhanice is a small municipality and village in the Central Bohemian Region of the Czech Republic.
-
D.
Pohořelice
Pohořelice is a small town in the South Moravian Region of the Czech Republic, known for its agricultural surroundings and proximity to the city of Brno.
-
E.
Moravice
Moravice is a river in the northern part of the historical Moravia region of the Czech Republic.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e0161ac8190aa1d52c063c02ad0 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff219635b08190a19dcaeb72240379 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:17 a.m.