Triple
T17243527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zala County |
E418562
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Somogy County |
E234838
|
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: Somogy County | Statement: [Zala County, borders, Somogy County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Somogy County Context triple: [Zala County, borders, Somogy County]
-
A.
Somogy County
chosen
Somogy County is an administrative region in southwestern Hungary, known for its rural landscapes and proximity to Lake Balaton.
-
B.
Zólyom County
Zólyom County was a historic administrative county of the Kingdom of Hungary, located in what is now central Slovakia around the town of Zvolen.
-
C.
Fejér County
Fejér County is an administrative region in central Hungary known for its historical significance and industrial centers, with Székesfehérvár as its county seat.
-
D.
Tolna County
Tolna County is an administrative region in central Hungary known for its agricultural landscape and location along the Danube River.
-
E.
Gömör-Kishont County
Gömör-Kishont County was a historic administrative county of the Kingdom of Hungary, located in what is today southern Slovakia and northern Hungary.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e21bb5c8190ad960f231fe54665 |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170f388608190b709b1c228a7ba29 |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:39 a.m.