Triple
T808598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bratislava |
E17491
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object |
Pozsony
Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
|
E126688
|
NE FINISHED |
How this triple was built (4 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: Pozsony | Statement: [Bratislava, historicalName, Pozsony]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pozsony Context triple: [Bratislava, historicalName, Pozsony]
-
A.
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.
-
B.
Sopron
Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
-
C.
Budapest
Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
-
D.
Kežmarok
Kežmarok is a historic town in northern Slovakia known for its well-preserved medieval architecture and role as a cultural center of the Spiš (Spisz) region.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pozsony Triple: [Bratislava, historicalName, Pozsony]
Generated description
Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pozsony Target entity description: Pozsony is the historical Hungarian name for the city now known as Bratislava, the capital of Slovakia.
-
A.
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.
-
B.
Sopron
Sopron is a historic city in western Hungary near the Austrian border, known for its well-preserved medieval old town and wine-making traditions.
-
C.
Budapest
Budapest is the capital and largest city of Hungary, renowned for its historic architecture, thermal baths, and prominent location along the Danube River.
-
D.
Kežmarok
Kežmarok is a historic town in northern Slovakia known for its well-preserved medieval architecture and role as a cultural center of the Spiš (Spisz) region.
-
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. chosen
Provenance (5 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab256cbc8190bf75b5d5e35ff0aa |
completed | March 1, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4bfac5cc8190a5fba1c5da98391d |
completed | March 7, 2026, 4:02 p.m. |
| NEDg | Description generation | batch_69ac4d1d58ac8190b1fc39a28aff8c46 |
completed | March 7, 2026, 4:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac4d90c3dc819092f6be4888851477 |
completed | March 7, 2026, 4:08 p.m. |
Created at: March 1, 2026, 7:38 p.m.