Triple
T14247424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oktogon station |
E353171
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Terézváros |
E857876
|
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: Terézváros | Statement: [Oktogon station, locatedIn, Terézváros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terézváros Context triple: [Oktogon station, locatedIn, Terézváros]
-
A.
Terézváros
chosen
Terézváros is a central district of Budapest, Hungary, known for its historic architecture, cultural venues, and vibrant urban life.
-
B.
Erzsébetváros
Erzsébetváros is a central Budapest district known for its historic Jewish Quarter, vibrant nightlife, and dense concentration of bars, restaurants, and cultural venues.
-
C.
Józsefváros
Józsefváros is a central district of Budapest, Hungary, known for its historic urban neighborhoods and ongoing revitalization.
-
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 13th district
Budapest 13th district is a central, densely populated district of Hungary’s capital, known for its mix of residential neighborhoods, business areas, and sections along the Danube River.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de629464f88190817b190731bab156 |
completed | April 14, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe387f28688190b9d20f1e2bbc0ddc |
completed | May 8, 2026, 7:24 p.m. |
Created at: April 10, 2026, 1:08 a.m.