Triple
T5598675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford, England |
E147059
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Budaörs
Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
|
E542675
|
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: Budaörs | Statement: [Bedford, England, hasTwinTown, Budaörs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Budaörs Context triple: [Bedford, England, hasTwinTown, Budaörs]
-
A.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
B.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
C.
Siófok
Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
-
D.
Győr
Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
-
E.
Zalaegerszeg
Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
- 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: Budaörs Triple: [Bedford, England, hasTwinTown, Budaörs]
Generated description
Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Budaörs Target entity description: Budaörs is a suburban town near Budapest in Hungary, known for its rapid post-communist development and role as a commercial and residential hub.
-
A.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
B.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
C.
Siófok
Siófok is a popular resort town on the southern shore of Lake Balaton in Hungary, known for its beaches and vibrant summer tourism.
-
D.
Győr
Győr is a historic city in northwestern Hungary, known as an important regional cultural and economic center at the confluence of the Danube, Rába, and Rábca rivers.
-
E.
Zalaegerszeg
Zalaegerszeg is a city in western Hungary that serves as the administrative center of Zala County and a regional economic and cultural hub.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020d82870819087f9591b5a1021ce |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a045c4881909a3e48a242db5d22 |
completed | March 22, 2026, 9:07 p.m. |
| NEDg | Description generation | batch_69c0767654a48190889caeb87fae7eef |
completed | March 22, 2026, 11:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c076e332d48190bd36ec9a1705602f |
completed | March 22, 2026, 11:10 p.m. |
Created at: March 22, 2026, 3:38 p.m.