Triple

T3337319
Position Surface form Disambiguated ID Type / Status
Subject Maputo E70168 entity
Predicate climateClassification P193 FINISHED
Object Köppen Aw E97834 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: Köppen Aw | Statement: [Maputo, climateClassification, Köppen Aw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Köppen Aw
Context triple: [Maputo, climateClassification, Köppen Aw]
  • A. Köppen Aw chosen
    Köppen Aw is a tropical savanna climate type characterized by consistently warm temperatures and a pronounced dry season.
  • B. Köppen BWh
    Köppen BWh is the hot desert climate subtype characterized by extremely low annual precipitation, very high temperatures, and abundant sunshine, typical of the world’s driest desert regions.
  • C. Köppen BWk
    Köppen BWk is a cold semi-arid (steppe) climate type characterized by low precipitation, hot summers, and cold winters, typically found in continental interior regions.
  • D. Köppen Am
    Köppen Am is a tropical monsoon climate type characterized by consistently high temperatures and a pronounced wet season with heavy rainfall.
  • E. Af (Köppen)
    Af (Köppen) is the tropical rainforest climate classification characterized by consistently high temperatures and abundant year-round rainfall with no dry season.
  • 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_69ad85a24f208190bcf83131bfed3521 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1bc31b4819085f01e0b5a7cbc5d completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a8ad1a8819081d7ad2a48e2c5b9 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:12 p.m.