Triple
T21354454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Túr River |
E526577
|
entity |
| Predicate | hasMouthNear |
P350
|
FINISHED |
| Object |
Vásárosnamény
Vásárosnamény is a town in northeastern Hungary known as a local regional center near the confluence of several rivers and close to the Ukrainian border.
|
E1483502
|
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: Vásárosnamény | Statement: [Túr River, hasMouthNear, Vásárosnamény]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vásárosnamény Context triple: [Túr River, hasMouthNear, Vásárosnamény]
-
A.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
B.
Vasvár
Vasvár is a small historic town in western Hungary known for its medieval heritage and role as a former county seat.
-
C.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
D.
Mencshely
Mencshely is a small village in Veszprém County, Hungary, situated near Lake Balaton within the Balatonfüred District.
-
E.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
- 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: Vásárosnamény Triple: [Túr River, hasMouthNear, Vásárosnamény]
Generated description
Vásárosnamény is a town in northeastern Hungary known as a local regional center near the confluence of several rivers and close to the Ukrainian border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vásárosnamény Target entity description: Vásárosnamény is a town in northeastern Hungary known as a local regional center near the confluence of several rivers and close to the Ukrainian border.
-
A.
Nagyvázsony
Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
-
B.
Vasvár
Vasvár is a small historic town in western Hungary known for its medieval heritage and role as a former county seat.
-
C.
Tiszaújváros
Tiszaújváros is an industrial town in northeastern Hungary known for its large chemical and energy industries and its location along the Tisza River.
-
D.
Mencshely
Mencshely is a small village in Veszprém County, Hungary, situated near Lake Balaton within the Balatonfüred District.
-
E.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8af9aa9508190b756cc8e07084c8e |
completed | April 22, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c2933f4c819093f9e39fd49f020a |
completed | May 17, 2026, 1:28 p.m. |
| NEDg | Description generation | batch_6a09c38ffc788190b2e1922da2d0cf2d |
completed | May 17, 2026, 1:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09c41d5e448190b18f8753c05e47cf |
completed | May 17, 2026, 1:35 p.m. |
Created at: April 16, 2026, 5:05 p.m.