Triple

T18763188
Position Surface form Disambiguated ID Type / Status
Subject Southern Namibia E458826 entity
Predicate hasTown P847 FINISHED
Object Karasburg 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: Karasburg | Statement: [Southern Namibia, hasTown, Karasburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karasburg
Context triple: [Southern Namibia, hasTown, Karasburg]
  • A. Karasburg chosen
    Karasburg is a small town in southern Namibia that serves as a local commercial and transport hub near the South African border.
  • B. Phillippsburg
    Phillippsburg is a historic town in southwestern Germany, known for its strategic fortress on the Rhine and its role in various European military conflicts.
  • C. Labpur
    Labpur is a town and administrative center in the Birbhum district of West Bengal, India, known for its rural cultural heritage and local markets.
  • D. Kotara
    Kotara is a suburb of Newcastle in New South Wales, Australia, known for its residential areas and major retail and commercial centres.
  • E. Carcoar
    Carcoar is a historic village in New South Wales, Australia, known for its well-preserved 19th-century architecture and picturesque rural setting.
  • 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e58d80a954819083946dafc0c7af05 completed April 20, 2026, 2:20 a.m.
Created at: April 10, 2026, 11:52 a.m.