Triple

T5034913
Position Surface form Disambiguated ID Type / Status
Subject Transdanubia E113398 entity
Predicate containsCity P294 FINISHED
Object Nagykanizsa E337046 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: Nagykanizsa | Statement: [Transdanubia, containsCity, Nagykanizsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nagykanizsa
Context triple: [Transdanubia, 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. 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.
  • D. Canyon
    Canyon is a 1959 abstract expressionist painting by Helen Frankenthaler, known for its innovative soak-stain technique and luminous color fields.
  • E. Canyon
    Canyon is a famous 1959 combine painting by Robert Rauschenberg that merges traditional painting with found objects, including a stuffed bald eagle, exemplifying his radical blurring of art and everyday materials.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b8646c8190b3cc20193e4639ee completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c759c608190875b6d48d99024b4 completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:36 p.m.