Triple
T11704136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felvidék |
E278196
|
entity |
| Predicate | hasCulturalRegion |
P1968
|
FINISHED |
| Object | Csallóköz (partly) |
E941838
|
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: Csallóköz (partly) | Statement: [Felvidék, hasCulturalRegion, Csallóköz (partly)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Csallóköz (partly) Context triple: [Felvidék, hasCulturalRegion, Csallóköz (partly)]
-
A.
Csallóköz
chosen
Csallóköz is a large river island and historical region in southwestern Slovakia, situated between branches of the Danube and known for its fertile land and significant freshwater resources.
-
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.
Nagykőrös
Nagykőrös is a historic town in central Hungary known for its agricultural traditions and small-town character.
-
D.
Püspökladány
Püspökladány is a town in eastern Hungary known for its location on the Great Hungarian Plain and its role as a local agricultural and transport hub.
-
E.
Kiskunhalas
Kiskunhalas is a town in southern Hungary known for its traditional lace-making and agricultural economy.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49b1080819096593733ee48a187 |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0195739348190b40a378ca227cf85 |
completed | April 28, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:40 p.m.