Triple
T9685726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bodrog |
E234401
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Sárospatak |
E685982
|
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: Sárospatak | Statement: [Bodrog, passesNear, Sárospatak]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sárospatak Context triple: [Bodrog, passesNear, Sárospatak]
-
A.
Sárospatak
chosen
Sárospatak is a historic town in northeastern Hungary, renowned for its medieval castle and role as a cultural and educational center in the region.
-
B.
Hévíz
Hévíz is a Hungarian spa town famous for its large natural thermal lake and wellness tourism.
-
C.
Balatonlelle
Balatonlelle is a popular Hungarian holiday town on the southern shore of Lake Balaton, known for its beaches, family-friendly attractions, and lakeside resorts.
-
D.
Balatonalmádi
Balatonalmádi is a popular Hungarian resort town on the northern shore of Lake Balaton, known for its beaches, holiday facilities, and scenic surroundings.
-
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_69ca84ca73208190957a900c8543bdcc |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9cd0877c81909fde1989d946aae9 |
completed | April 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1910b7c148190b9061b1ce0520e8b |
completed | April 4, 2026, 10:30 p.m. |
Created at: March 30, 2026, 8:16 p.m.