Triple

T536170
Position Surface form Disambiguated ID Type / Status
Subject Zambezi River E12331 entity
Predicate flowsThrough P225 FINISHED
Object Caprivi Strip E14828 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: Caprivi Strip | Statement: [Zambezi River, flowsThrough, Caprivi Strip]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caprivi Strip
Context triple: [Zambezi River, flowsThrough, Caprivi Strip]
  • A. Katavi Region
    Katavi Region is a sparsely populated administrative region in western Tanzania known for its vast wilderness areas and the wildlife-rich Katavi National Park.
  • B. Namibia chosen
    Namibia is a sparsely populated country in southwestern Africa known for its dramatic desert landscapes, diverse wildlife, and a legal system influenced by Roman-Dutch law.
  • C. Congo
    Congo is a Central African country whose economy is heavily reliant on oil production and exports.
  • D. Northwestern Zambia
    Northwestern Zambia is a sparsely populated, rural region of Zambia known for its upland plateaus, extensive forests, and role as a headwaters area for major southern African rivers.
  • E. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a496da8e108190b4874c3b85290464 completed March 1, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ed30d578819091c6c1f4c5eba301 completed March 2, 2026, 1:51 a.m.
Created at: March 1, 2026, 7:32 p.m.