Triple
T13556935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ondava |
E323798
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object | Topľa |
E315955
|
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: Topľa | Statement: [Ondava, hasTributary, Topľa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Topľa Context triple: [Ondava, hasTributary, Topľa]
-
A.
Topľa
chosen
Topľa is a river in eastern Slovakia that flows through the Prešov Region before joining the Ondava River.
-
B.
Vrútky
Vrútky is a town in northern Slovakia that serves as an important railway junction and gateway between central and northern regions of the country.
-
C.
Vatreni
Vatreni is the popular nickname of the Croatia national football team, renowned for its passionate, high-intensity style of play and strong performances in major international tournaments.
-
D.
Toplița
Toplița is a town in central Romania known for its mountainous surroundings, thermal springs, and winter sports opportunities.
-
E.
Znamianka
Znamianka is a city in central Ukraine that serves as an important regional railway junction and administrative center within Kirovohrad Oblast.
- 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_69d8076830b48190910a902bae5888e2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaff3063c8190bd20149b3f7df352 |
completed | April 12, 2026, 2:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75da95b7c8190af4fae155f01d3af |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:47 p.m.