Triple

T23460412
Position Surface form Disambiguated ID Type / Status
Subject Panda District E568956 entity
Predicate locatedInTimeZone P109 FINISHED
Object Africa/Maputo 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: Africa/Maputo | Statement: [Panda District, locatedInTimeZone, Africa/Maputo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Africa/Maputo
Context triple: [Panda District, locatedInTimeZone, Africa/Maputo]
  • A. Africa/Maputo chosen
    Africa/Maputo is a time zone corresponding to Central Africa Time (UTC+2), used by several countries in southeastern Africa including Mozambique.
  • B. Nampula
    Nampula is a major city in northern Mozambique that serves as an important commercial and transportation hub for the region.
  • C. Beira
    Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
  • D. Port of Maputo
    The Port of Maputo is Mozambique’s principal deep-water seaport and a major regional hub for maritime trade in southeastern Africa.
  • E. Johannesburg–Maputo
    Johannesburg–Maputo is an international air route linking Johannesburg, South Africa with Maputo, the capital of Mozambique.
  • 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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a69afba88190b1b1dd27d331309f completed April 29, 2026, 6:35 a.m.
Created at: April 17, 2026, 5:53 p.m.