Triple
T16765972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fertő-Hanság National Park |
E407463
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lake Fertő |
E1143494
|
NE FINISHED |
How this triple was built (2 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: Lake Fertő | Statement: [Fertő-Hanság National Park, hasPart, Lake Fertő]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Fertő Context triple: [Fertő-Hanság National Park, hasPart, Lake Fertő]
-
A.
Fertő-tó
chosen
Fertő-tó is a large steppe lake on the Austrian–Hungarian border, renowned for its unique wetland ecosystem, birdlife, and surrounding cultural landscape.
-
B.
Lake Balaton
Lake Balaton is a major Central European freshwater lake in western Hungary, renowned as a popular tourist and recreation destination.
-
C.
Sárospatak
Sárospatak is a historic town in northeastern Hungary, renowned for its medieval castle and role as a cultural and educational center in the region.
-
D.
Lake Neusiedl
Lake Neusiedl is a large, shallow steppe lake in Central Europe renowned for its unique wetland ecosystem, birdlife, and surrounding wine-growing region.
-
E.
Bodrog
Bodrog is a river in Central Europe that flows through Slovakia and Hungary before joining the Tisza River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b0330d6081908ce99f14c70b90f2 |
completed | April 18, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a531ea7c81908630f16f6c685d49 |
completed | May 10, 2026, 3:33 p.m. |
Created at: April 10, 2026, 5:21 a.m.