Triple
T9096519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zala River |
E218034
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object | Zalaegerszeg |
E423178
|
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: Zalaegerszeg | Statement: [Zala River, hasCityOnRiver, Zalaegerszeg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zalaegerszeg Context triple: [Zala River, hasCityOnRiver, Zalaegerszeg]
-
A.
Zalaegerszeg
chosen
Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
-
B.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
C.
Szeged
Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
-
D.
Szekszárd
Szekszárd is a historic Hungarian town renowned as one of the country’s leading red wine regions and the administrative center of Tolna County.
-
E.
Győr
Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b7d0d48190a3b15f35bef087e3 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1820133348190a25ba1ab3fc7359d |
completed | April 4, 2026, 9:26 p.m. |
Created at: March 30, 2026, 7:15 p.m.