Triple

T7681164
Position Surface form Disambiguated ID Type / Status
Subject Sperrgebiet National Park E173995 entity
Predicate contains P35 FINISHED
Object Kolmanskop E163851 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: Kolmanskop | Statement: [Sperrgebiet National Park, contains, Kolmanskop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kolmanskop
Context triple: [Sperrgebiet National Park, contains, Kolmanskop]
  • A. Kolmanskop chosen
    Kolmanskop is a famous ghost town in Namibia’s Namib Desert, once a prosperous German colonial diamond mining settlement now known for its sand-filled, abandoned buildings.
  • B. Karoi
    Karoi is a small agricultural and commercial town in northern Zimbabwe known as a service center for the surrounding tobacco-growing region.
  • C. Kraaifontein
    Kraaifontein is a residential suburb in the northern outskirts of Cape Town, South Africa, known for its mixed urban and semi-rural character.
  • D. Bela-Bela
    Bela-Bela is a South African town in Limpopo Province known for its natural hot mineral springs and tourism-focused resorts.
  • E. Hazyview
    Hazyview is a small South African town in Mpumalanga known as a gateway to Kruger National Park and the scenic attractions of the surrounding Lowveld.
  • 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_69c6995840408190a19de6c51090f46f completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701ffc1fc8190bc9c2b1f3bb37f0d completed March 27, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8a24de3a48190a92009b6092b09d0 completed March 29, 2026, 3:53 a.m.
Created at: March 27, 2026, 4:01 p.m.