Triple
T2103595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tisza |
E37143
|
entity |
| Predicate | flowsThroughCity |
P10456
|
FINISHED |
| Object |
Tokaj
Tokaj is a historic town in northeastern Hungary renowned worldwide for its Tokaji wine region and sweet dessert wines.
|
E234399
|
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: Tokaj | Statement: [Tisza, flowsThroughCity, Tokaj]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tokaj Context triple: [Tisza, flowsThroughCity, Tokaj]
-
A.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
B.
Keszthely
Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
-
C.
Sátoraljaújhely
Sátoraljaújhely is a historic town in northeastern Hungary near the Slovak border, known for its wine region, cultural heritage, and scenic Zemplén Mountains setting.
-
D.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
E.
Tatabánya
Tatabánya is an industrial city in northwestern Hungary known for its mining heritage and role as a regional economic center.
- 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: Tokaj Triple: [Tisza, flowsThroughCity, Tokaj]
Generated description
Tokaj is a historic town in northeastern Hungary renowned worldwide for its Tokaji wine region and sweet dessert wines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tokaj Target entity description: Tokaj is a historic town in northeastern Hungary renowned worldwide for its Tokaji wine region and sweet dessert wines.
-
A.
Kaposvár
Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
-
B.
Keszthely
Keszthely is a historic town in western Hungary known for its lakeside resort atmosphere, cultural heritage, and proximity to Lake Balaton.
-
C.
Sátoraljaújhely
Sátoraljaújhely is a historic town in northeastern Hungary near the Slovak border, known for its wine region, cultural heritage, and scenic Zemplén Mountains setting.
-
D.
Gödöllő
Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
-
E.
Tatabánya
Tatabánya is an industrial city in northwestern Hungary known for its mining heritage and role as a regional economic center.
- 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_69a8861828948190924aa30c08806b3a |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abbabf7cdc81909636dff34badc1c5 |
completed | March 7, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae3069f78c819092a6d9d903e4df13 |
completed | March 9, 2026, 2:28 a.m. |
| NEDg | Description generation | batch_69ae311eec148190af10e88fb4d7c433 |
completed | March 9, 2026, 2:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae3199909881909ffca021098c98ea |
completed | March 9, 2026, 2:34 a.m. |
Created at: March 4, 2026, 7:43 p.m.