Triple
T15077408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bückeburg |
E380040
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Tiszakécske
Tiszakécske is a town in central Hungary known for its location along the Tisza River and its thermal baths.
|
E1198385
|
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: Tiszakécske | Statement: [Bückeburg, hasTwinTown, Tiszakécske]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiszakécske Context triple: [Bückeburg, hasTwinTown, Tiszakécske]
-
A.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
B.
Kőszeg
Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
-
C.
Nagykálló
Nagykálló is a town in northeastern Hungary known for its historical architecture and traditional cultural heritage.
-
D.
Kiskőrös
Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
-
E.
Egerszalók
Egerszalók is a Hungarian village famous for its thermal springs and striking terraced salt hill spa complex.
- 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: Tiszakécske Triple: [Bückeburg, hasTwinTown, Tiszakécske]
Generated description
Tiszakécske is a town in central Hungary known for its location along the Tisza River and its thermal baths.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tiszakécske Target entity description: Tiszakécske is a town in central Hungary known for its location along the Tisza River and its thermal baths.
-
A.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
B.
Kőszeg
Kőszeg is a historic Hungarian town near the Austrian border, renowned for its well-preserved medieval architecture and role in defending against Ottoman sieges.
-
C.
Nagykálló
Nagykálló is a town in northeastern Hungary known for its historical architecture and traditional cultural heritage.
-
D.
Kiskőrös
Kiskőrös is a small town in southern Hungary known as the birthplace of the national poet Sándor Petőfi and for its wine-producing region.
-
E.
Egerszalók
Egerszalók is a Hungarian village famous for its thermal springs and striking terraced salt hill spa complex.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fe5a208190823900b25e298dab |
completed | April 15, 2026, 8:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff78dab488190a89b9eb4f648b36c |
completed | May 10, 2026, 3:12 a.m. |
| NEDg | Description generation | batch_69fffb6d9f90819095c5d1a70b5c90a3 |
completed | May 10, 2026, 3:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fffbc0376c8190a9cae5dc3d941471 |
completed | May 10, 2026, 3:30 a.m. |
Created at: April 10, 2026, 3:03 a.m.