Triple
T2094755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fejér County |
E32753
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
|
E244359
|
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: Csákvár | Statement: [Fejér County, containsTown, Csákvár]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Csákvár Context triple: [Fejér County, containsTown, Csákvár]
-
A.
Komló
Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
-
B.
Bicske
Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
-
C.
Sárbogárd
Sárbogárd is a small town in central Hungary known for its agricultural surroundings and role as a local transport hub within Fejér County.
-
D.
Dunaújváros
Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
-
E.
Keszthely
Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
- 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: Csákvár Triple: [Fejér County, containsTown, Csákvár]
Generated description
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Csákvár Target entity description: Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
-
A.
Komló
Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
-
B.
Bicske
Bicske is a small town in central Hungary known for its historical significance and location along major transportation routes west of Budapest.
-
C.
Sárbogárd
Sárbogárd is a small town in central Hungary known for its agricultural surroundings and role as a local transport hub within Fejér County.
-
D.
Dunaújváros
Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
-
E.
Keszthely
Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
- 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_69a885eba0708190999696a45cbec816 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abba99ddc48190bb2097b56efb7aca |
completed | March 7, 2026, 5:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae652ce3108190999ce10fe915aba1 |
completed | March 9, 2026, 6:14 a.m. |
| NEDg | Description generation | batch_69ae6608d3ac8190923cd6a6ce7c4c89 |
completed | March 9, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae66a751f881908fda164de72dac9b |
completed | March 9, 2026, 6:20 a.m. |
Created at: March 4, 2026, 7:43 p.m.