Triple
T12825129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiszaújváros |
E306629
|
entity |
| Predicate | previousName |
P65
|
FINISHED |
| Object |
Leninváros
Leninváros was the former name of the Hungarian industrial town now known as Tiszaújváros, developed during the socialist era.
|
E1004455
|
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: Leninváros | Statement: [Tiszaújváros, previousName, Leninváros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leninváros Context triple: [Tiszaújváros, previousName, Leninváros]
-
A.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
B.
Livny
Livny is a historic town in western Russia known as one of the principal urban centers of Oryol Oblast.
-
C.
Stockheim
Stockheim is a village and district of the town of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
-
D.
Kingissepa
Kingissepa is the former Soviet-era name of the Estonian town now known as Kuressaare, located on Saaremaa Island.
-
E.
Lennestadt
Lennestadt is a town in the Olpe district of North Rhine-Westphalia, Germany, known for its location in the hilly, forested Sauerland region and its mix of industry and tourism.
- 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: Leninváros Triple: [Tiszaújváros, previousName, Leninváros]
Generated description
Leninváros was the former name of the Hungarian industrial town now known as Tiszaújváros, developed during the socialist era.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Leninváros Target entity description: Leninváros was the former name of the Hungarian industrial town now known as Tiszaújváros, developed during the socialist era.
-
A.
Tivissa
Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
-
B.
Livny
Livny is a historic town in western Russia known as one of the principal urban centers of Oryol Oblast.
-
C.
Stockheim
Stockheim is a village and district of the town of Brackenheim in the Heilbronn district of Baden-Württemberg, Germany.
-
D.
Kingissepa
Kingissepa is the former Soviet-era name of the Estonian town now known as Kuressaare, located on Saaremaa Island.
-
E.
Lennestadt
Lennestadt is a town in the Olpe district of North Rhine-Westphalia, Germany, known for its location in the hilly, forested Sauerland region and its mix of industry and tourism.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96facb2d48190bc12efc00c9da360 |
completed | April 10, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed4f7388190ba989b8a79bd7c6d |
completed | May 2, 2026, 11:55 p.m. |
| NEDg | Description generation | batch_69f691341d0081909ca3b281ee64b42b |
completed | May 3, 2026, 12:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f692361c3c81909078a19be1a86231 |
completed | May 3, 2026, 12:09 a.m. |
Created at: April 9, 2026, 5:32 p.m.