Triple
T9090305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaposvár |
E217864
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Kapos River |
E365576
|
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: Kapos River | Statement: [Kaposvár, namedAfter, Kapos River]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kapos River Context triple: [Kaposvár, namedAfter, Kapos River]
-
A.
Kapos River
chosen
The Kapos River is a waterway in southwestern Hungary that flows through the city of Kaposvár before joining the Sió River.
-
B.
Diep River
Diep River is a river in the Western Cape of South Africa that flows through the Cape Town area, including the suburb of Milnerton, before reaching the Atlantic Ocean.
-
C.
Ganja River
The Ganja River is a waterway in western Azerbaijan that flows through the city of Ganja (historically Elisavetpol), contributing to the region’s geography and settlement.
-
D.
Black River
Black River is a coastal town in Cornwall County, Jamaica, historically known as one of the island’s oldest ports and an early adopter of electricity.
-
E.
Black River
Black River is a common river name used in various regions worldwide, typically referring to waterways characterized by dark-colored water due to organic matter or sediment.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc965971f88190acffbf204c11832b |
completed | April 1, 2026, 3:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d03007ed908190afd34cf3f32312e9 |
completed | April 3, 2026, 9:24 p.m. |
Created at: March 30, 2026, 7:14 p.m.