Triple
T9096521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zala River |
E218034
|
entity |
| Predicate | hasCityOnRiver |
P17819
|
FINISHED |
| Object |
Zalakomár
Zalakomár is a village in southwestern Hungary known for its rural character and proximity to the Zala River and nearby wetlands.
|
E777897
|
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: Zalakomár | Statement: [Zala River, hasCityOnRiver, Zalakomár]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zalakomár Context triple: [Zala River, hasCityOnRiver, Zalakomár]
-
A.
Zamárdi
Zamárdi is a popular Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, lakeside recreation, and summer festivals.
-
B.
Kozármisleny
Kozármisleny is a small town in southern Hungary, near Pécs, known for its growing residential character and local sports culture.
-
C.
Mátraháza
Mátraháza is a small mountain resort village in northern Hungary, known for its scenic location in the Mátra range and its hiking and wellness tourism.
-
D.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
-
E.
Szatmár
Szatmár is the Hungarian name for Satu Mare, a historic city in northwestern Romania near the Hungarian border.
- 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: Zalakomár Triple: [Zala River, hasCityOnRiver, Zalakomár]
Generated description
Zalakomár is a village in southwestern Hungary known for its rural character and proximity to the Zala River and nearby wetlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zalakomár Target entity description: Zalakomár is a village in southwestern Hungary known for its rural character and proximity to the Zala River and nearby wetlands.
-
A.
Zamárdi
Zamárdi is a popular Hungarian resort town on the southern shore of Lake Balaton, known for its beaches, lakeside recreation, and summer festivals.
-
B.
Kozármisleny
Kozármisleny is a small town in southern Hungary, near Pécs, known for its growing residential character and local sports culture.
-
C.
Mátraháza
Mátraháza is a small mountain resort village in northern Hungary, known for its scenic location in the Mátra range and its hiking and wellness tourism.
-
D.
Csákvár
Csákvár is a small town in central Hungary known for its rural character and location within the Transdanubian region.
-
E.
Szatmár
Szatmár is the Hungarian name for Satu Mare, a historic city in northwestern Romania near the Hungarian border.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc96b7d0d48190a3b15f35bef087e3 |
completed | April 1, 2026, 3:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0180f70b88190a2d3dc49f32f0c2e |
completed | April 3, 2026, 7:42 p.m. |
| NEDg | Description generation | batch_69d019652fe8819096cccb8cff431261 |
completed | April 3, 2026, 7:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d01a290de881909482b7eb70bef0e3 |
completed | April 3, 2026, 7:51 p.m. |
Created at: March 30, 2026, 7:15 p.m.