Triple
T14864825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Széchényi Library |
E349589
|
entity |
| Predicate | collectionType |
P121
|
FINISHED |
| Object |
Hungarica
Hungarica refers to publications and documents related to Hungary or Hungarians, regardless of where they were produced.
|
E1127716
|
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: Hungarica | Statement: [National Széchényi Library, collectionType, Hungarica]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hungarica Context triple: [National Széchényi Library, collectionType, Hungarica]
-
A.
Ungar
Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
-
B.
Poroszló
Poroszló is a village in northern Hungary situated near Lake Tisza, known for its natural surroundings and eco-tourism opportunities.
-
C.
Ungarie
Ungarie is a small rural town in New South Wales, Australia, known for its agricultural community and location within the Bland Shire local government area.
-
D.
Hungary
Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
-
E.
Havran
Havran is a town and district in western Turkey known for its agricultural production and location within Balıkesir Province.
- 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: Hungarica Triple: [National Széchényi Library, collectionType, Hungarica]
Generated description
Hungarica refers to publications and documents related to Hungary or Hungarians, regardless of where they were produced.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hungarica Target entity description: Hungarica refers to publications and documents related to Hungary or Hungarians, regardless of where they were produced.
-
A.
Ungar
Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
-
B.
Poroszló
Poroszló is a village in northern Hungary situated near Lake Tisza, known for its natural surroundings and eco-tourism opportunities.
-
C.
Ungarie
Ungarie is a small rural town in New South Wales, Australia, known for its agricultural community and location within the Bland Shire local government area.
-
D.
Hungary
Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
-
E.
Havran
Havran is a town and district in western Turkey known for its agricultural production and location within Balıkesir Province.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded574d0ec8190a6afed672ba6c2f9 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72aad76c8190b024651483d8f9ff |
completed | May 8, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69fe7b078d0c8190ba80b6e96975fd6c |
completed | May 9, 2026, 12:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe7b26519c8190ba81d997e11a999f |
completed | May 9, 2026, 12:09 a.m. |
Created at: April 10, 2026, 1:54 a.m.