Triple
T19512062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunántúl |
E488179
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Nagykanizsa |
—
|
NE NERFINISHED |
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: Nagykanizsa | Statement: [Dunántúl, containsCity, Nagykanizsa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nagykanizsa Context triple: [Dunántúl, containsCity, Nagykanizsa]
-
A.
Nagykanizsa
chosen
Nagykanizsa is a city in southwestern Hungary known historically as a regional commercial and cultural center.
-
B.
Κανὰ
Κανὰ is the Greek name for Cana, the Galilean village traditionally associated with Jesus’ first miracle of turning water into wine.
-
C.
Bighorn Canyon
Bighorn Canyon is a dramatic, steep-walled gorge carved by the Bighorn River, renowned for its striking desert-and-cliff landscapes and recreational opportunities in the Bighorn Canyon National Recreation Area.
-
D.
Boulder Canyon
Boulder Canyon is a rugged river gorge on the Colorado River in the American Southwest, historically significant in early plans for dam and hydroelectric development in the region.
-
E.
Canyon
Canyon is a 1959 abstract expressionist painting by Helen Frankenthaler, known for its innovative soak-stain technique and luminous color fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359908fc8190bd05f26d4271d268 |
completed | April 20, 2026, 2:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.