Triple
T13621942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arad |
E325477
|
entity |
| Predicate | twinnedWith |
P1072
|
FINISHED |
| Object | Hódmezővásárhely |
E326247
|
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: Hódmezővásárhely | Statement: [Arad, twinnedWith, Hódmezővásárhely]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hódmezővásárhely Context triple: [Arad, twinnedWith, Hódmezővásárhely]
-
A.
Hódmezővásárhely
chosen
Hódmezővásárhely is a city in southeastern Hungary known for its agricultural traditions, pottery, and regional cultural heritage.
-
B.
Dombóvár
Dombóvár is a town in southern Hungary known as an important local transport and economic center within Tolna County.
-
C.
Gyulafehérvár
Gyulafehérvár, known today as Alba Iulia in Romania, is a historic city that served as the political and cultural center of Transylvania for centuries.
-
D.
Kalocsa
Kalocsa is a historic town in southern Hungary known as an important Roman Catholic archiepiscopal center and for its traditional paprika production and folk art.
-
E.
Hajdúszoboszló
Hajdúszoboszló is a Hungarian spa town renowned for its thermal baths and large water park, making it a major health and wellness tourism destination.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbe99ddc08190a8d79107c8e176fa |
completed | April 12, 2026, 3:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b2e59e88190b58fdf9d9643aef9 |
completed | May 9, 2026, 10:23 a.m. |
Created at: April 9, 2026, 9:50 p.m.