Triple
T15557988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vrbas |
E370919
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Vrbanja
Vrbanja is a river in Bosnia and Herzegovina that flows through central parts of the country before joining the Vrbas River.
|
E1166463
|
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: Vrbanja | Statement: [Vrbas, hasTributary, Vrbanja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vrbanja Context triple: [Vrbas, hasTributary, Vrbanja]
-
A.
Vrbnik
Vrbnik is a historic coastal town on the Croatian island of Krk, known for its clifftop old town, narrow streets, and production of the Žlahtina white wine.
-
B.
Savski Venac
Savski Venac is a central urban municipality of Belgrade, Serbia, known for its government institutions, major transport hubs, and historic neighborhoods.
-
C.
Morača
Morača is a major river in Montenegro that flows through the capital city of Podgorica before emptying into Lake Skadar.
-
D.
Bosančica
Bosančica is a historical variant of the Cyrillic script that was used primarily in medieval Bosnia and neighboring regions for writing the Bosnian language.
-
E.
Grbavica
Grbavica is a neighborhood in Sarajevo, Bosnia and Herzegovina, known for its residential blocks and its association with local football culture.
- 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: Vrbanja Triple: [Vrbas, hasTributary, Vrbanja]
Generated description
Vrbanja is a river in Bosnia and Herzegovina that flows through central parts of the country before joining the Vrbas River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vrbanja Target entity description: Vrbanja is a river in Bosnia and Herzegovina that flows through central parts of the country before joining the Vrbas River.
-
A.
Vrbnik
Vrbnik is a historic coastal town on the Croatian island of Krk, known for its clifftop old town, narrow streets, and production of the Žlahtina white wine.
-
B.
Savski Venac
Savski Venac is a central urban municipality of Belgrade, Serbia, known for its government institutions, major transport hubs, and historic neighborhoods.
-
C.
Morača
Morača is a major river in Montenegro that flows through the capital city of Podgorica before emptying into Lake Skadar.
-
D.
Bosančica
Bosančica is a historical variant of the Cyrillic script that was used primarily in medieval Bosnia and neighboring regions for writing the Bosnian language.
-
E.
Grbavica
Grbavica is a neighborhood in Sarajevo, Bosnia and Herzegovina, known for its residential blocks and its association with local football culture.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dda3ab88190ab383333ce69fe8f |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56bf8cac81909886de5b82849cb2 |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff5752f3188190a70713ebbe928dff |
completed | May 9, 2026, 3:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff57d92abc81909cb63cfb51741116 |
completed | May 9, 2026, 3:50 p.m. |
Created at: April 10, 2026, 4:09 a.m.