Triple
T17014059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rába |
E412771
|
entity |
| Predicate | hasLeftTributary |
P415
|
FINISHED |
| Object | Zala |
E780731
|
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: Zala | Statement: [Rába, hasLeftTributary, Zala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zala Context triple: [Rába, hasLeftTributary, Zala]
-
A.
Zala
chosen
Zala is a river in western Hungary that flows into Lake Balaton and lends its name to the surrounding Zala region.
-
B.
Zugló
Zugló is Budapest’s 14th district, a largely residential area known for its parks, historic villas, and major landmarks such as City Park and Heroes’ Square.
-
C.
Trencsén
Trencsén is a historic town in present-day Slovakia, known for its medieval castle and its role as an important regional center in the former Upper Hungary.
-
D.
Zólyom
Zólyom is the historical Hungarian name for the Slovak town of Zvolen, an important medieval center in central Slovakia.
-
E.
Kolozsvar
Kolozsvár is the Hungarian name for Cluj-Napoca, a major cultural, academic, and economic center in northwestern Romania and the historical capital of Transylvania.
- 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_69d886cc4170819093deddc7b8b4b6a7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d47e64f081908f43870c7564d0ae |
completed | April 18, 2026, 6:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b4990948190861ff81f8fc3e8f2 |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 10, 2026, 5:33 a.m.