Triple

T14644324
Position Surface form Disambiguated ID Type / Status
Subject Malanje Province E343805 entity
Predicate touristAttraction P530 FINISHED
Object Kalandula Falls E1123394 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: Kalandula Falls | Statement: [Malanje Province, touristAttraction, Kalandula Falls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kalandula Falls
Context triple: [Malanje Province, touristAttraction, Kalandula Falls]
  • A. Kalandula Falls chosen
    Kalandula Falls is one of Africa’s largest and most impressive waterfalls, located on the Lucala River in Angola.
  • B. Krushuna Falls
    Krushuna Falls is a picturesque series of turquoise travertine waterfalls and pools located in northern Bulgaria, renowned for its lush forest setting and scenic hiking paths.
  • C. Afurdja Waterfall
    Afurdja Waterfall is a scenic natural cascade and popular tourist attraction located near the town of Quba in northeastern Azerbaijan.
  • D. Kakolat Falls
    Kakolat Falls is a scenic multi-tiered waterfall and popular tourist spot located near Nawada in the Indian state of Bihar.
  • E. Toraille Waterfall
    Toraille Waterfall is a popular scenic cascade and swimming spot in Saint Lucia, known for its lush rainforest setting and easy accessibility to visitors.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe7e7772508190bee1eb310aa40372 completed May 9, 2026, 12:23 a.m.
Created at: April 10, 2026, 1:26 a.m.