Triple
T710852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hungary–Austria border |
E14202
|
entity |
| Predicate | adjacentToCity |
P5707
|
FINISHED |
| Object | Szombathely |
E99815
|
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: Szombathely | Statement: [Hungary–Austria border, adjacentToCity, Szombathely]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Szombathely Context triple: [Hungary–Austria border, adjacentToCity, Szombathely]
-
A.
Szeged
Szeged is a prominent city in southern Hungary known for its university, paprika production, and distinctive Art Nouveau architecture.
-
B.
Miskolc
Miskolc is a large industrial and cultural city in northeastern Hungary, known for its steel industry, historic center, and nearby cave baths.
-
C.
Sopron
chosen
Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
-
D.
Pécs
Pécs is a historic cultural and university city in southwestern Hungary, renowned for its Roman and Ottoman heritage and its designation as a European Capital of Culture in 2010.
-
E.
Debrecen
Debrecen is Hungary’s second-largest city and a key cultural, economic, and educational center in the country’s eastern region.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a55c99fc8190941c5fd18551792a |
completed | March 1, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b83709248190bee17ec028b12bae |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:36 p.m.