Triple
T14148086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District V (Budapest) |
E350604
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Belváros |
E862789
|
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: Belváros | Statement: [District V (Budapest), hasPart, Belváros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belváros Context triple: [District V (Budapest), hasPart, Belváros]
-
A.
Terézváros
Terézváros is a central district of Budapest, Hungary, known for its historic architecture, cultural venues, and vibrant urban life.
-
B.
Lipótváros
Lipótváros is a historic central neighborhood of Budapest known for its grand 19th-century architecture, government buildings, and landmarks such as the Hungarian Parliament.
-
C.
Budaörs
Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
-
D.
Budapest II District
Budapest II District is a largely residential, affluent district on the Buda side of Hungary’s capital, known for its hilly terrain, green areas, and upscale neighborhoods.
-
E.
Budapest V. kerület
chosen
Budapest V. kerület is the central district of Budapest, known for housing key government buildings, historic landmarks, and major tourist attractions along the Danube.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61237ef481909374c1f68a2370b7 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd2802ba608190849313ff2661cd07 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 12:55 a.m.