Triple
T15295276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mura |
E365637
|
entity |
| Predicate | hasLeftTributary |
P415
|
FINISHED |
| Object |
Lendava
Lendava is a river in Central Europe that flows through northeastern Slovenia and western Hungary before joining the Mura River.
|
E1149078
|
NE FINISHED |
How this triple was built (4 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: Lendava | Statement: [Mura, hasLeftTributary, Lendava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lendava Context triple: [Mura, hasLeftTributary, Lendava]
-
A.
Lendava
Lendava is a small town in northeastern Slovenia near the Hungarian border, known for its multicultural heritage, historic castle, and spa tourism.
-
B.
Kobarid
Kobarid is a historic town in western Slovenia, known for its World War I heritage sites and scenic Alpine surroundings.
-
C.
Tolmin
Tolmin is a small Slovenian town in the Julian Alps, known as a gateway to the Soča Valley and for its scenic gorges, rivers, and outdoor recreation.
-
D.
Klanjec
Klanjec is a small town in northern Croatia’s Zagorje region, known for its historic architecture and picturesque rural surroundings.
-
E.
Lovran
Lovran is a historic coastal town on Croatia’s Adriatic Riviera, known for its Austro-Hungarian era villas, mild climate, and role as an early seaside resort.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lendava Triple: [Mura, hasLeftTributary, Lendava]
Generated description
Lendava is a river in Central Europe that flows through northeastern Slovenia and western Hungary before joining the Mura River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lendava Target entity description: Lendava is a river in Central Europe that flows through northeastern Slovenia and western Hungary before joining the Mura River.
-
A.
Lendava
Lendava is a small town in northeastern Slovenia near the Hungarian border, known for its multicultural heritage, historic castle, and spa tourism.
-
B.
Kobarid
Kobarid is a historic town in western Slovenia, known for its World War I heritage sites and scenic Alpine surroundings.
-
C.
Tolmin
Tolmin is a small Slovenian town in the Julian Alps, known as a gateway to the Soča Valley and for its scenic gorges, rivers, and outdoor recreation.
-
D.
Klanjec
Klanjec is a small town in northern Croatia’s Zagorje region, known for its historic architecture and picturesque rural surroundings.
-
E.
Lovran
Lovran is a historic coastal town on Croatia’s Adriatic Riviera, known for its Austro-Hungarian era villas, mild climate, and role as an early seaside resort.
- F. None of above. chosen
Provenance (5 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e036848c1881908fbaaae0216d6d27 |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef81058c8190aec7c7ad9a68f569 |
completed | May 9, 2026, 8:25 a.m. |
| NEDg | Description generation | batch_69fef36488e081909be34cf781af91ea |
completed | May 9, 2026, 8:42 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fef435b1208190bd839297a2f8d3f4 |
completed | May 9, 2026, 8:45 a.m. |
Created at: April 10, 2026, 3:15 a.m.