Triple
T9703625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pest County |
E234839
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Gyál
Gyál is a town in central Hungary that functions as a suburban residential area near Budapest within Pest County.
|
E818582
|
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: Gyál | Statement: [Pest County, hasSettlement, Gyál]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gyál Context triple: [Pest County, hasSettlement, Gyál]
-
A.
Gárdony
Gárdony is a Hungarian town and popular resort area on the southern shore of Lake Velence, known for its beaches, thermal waters, and recreational tourism.
-
B.
Somlyó
Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
-
C.
Zagyva
Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
-
D.
Zengő
Zengő is a prominent peak in southern Hungary known for its scenic hiking trails and panoramic views over the Mecsek mountain range.
-
E.
Zamárdi
Zamárdi is a popular Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, lakeside recreation, and summer festivals.
- 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: Gyál Triple: [Pest County, hasSettlement, Gyál]
Generated description
Gyál is a town in central Hungary that functions as a suburban residential area near Budapest within Pest County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gyál Target entity description: Gyál is a town in central Hungary that functions as a suburban residential area near Budapest within Pest County.
-
A.
Gárdony
Gárdony is a Hungarian town and popular resort area on the southern shore of Lake Velence, known for its beaches, thermal waters, and recreational tourism.
-
B.
Somlyó
Somlyó is a historical locality in the Kingdom of Hungary, best known as the birthplace of Stephen Báthory, who became King of Poland and Grand Duke of Lithuania in the 16th century.
-
C.
Zagyva
Zagyva is a river in northern Hungary that flows through towns such as Salgótarján and Hatvan before joining the Tisza River.
-
D.
Zengő
Zengő is a prominent peak in southern Hungary known for its scenic hiking trails and panoramic views over the Mecsek mountain range.
-
E.
Zamárdi
Zamárdi is a popular Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, lakeside recreation, and summer festivals.
- 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_69ca84cc78808190a56f3402b7c139a7 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d73a0148190ad4178fd462cdd9c |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1af93b76c81908377f17956fb86b1 |
completed | April 5, 2026, 12:40 a.m. |
| NEDg | Description generation | batch_69d1b08ba1f48190830852f9d60e3368 |
completed | April 5, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b124659481909e7a2ecaf01d8a50 |
completed | April 5, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:18 p.m.