Triple

T20995481
Position Surface form Disambiguated ID Type / Status
Subject Donald Woods E517136 entity
Predicate placeOfBirth P1 FINISHED
Object Transkei 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: Transkei | Statement: [Donald Woods, placeOfBirth, Transkei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transkei
Context triple: [Donald Woods, placeOfBirth, Transkei]
  • A. Transkei chosen
    Transkei was a former bantustan in southeastern South Africa, established under apartheid as a nominally self-governing territory primarily for Xhosa-speaking peoples.
  • B. Tiszanána
    Tiszanána is a village in northern Hungary known for its proximity to the Tisza River and recreational areas around Lake Tisza.
  • C. Transkei, South Africa
    Transkei, South Africa was a former bantustan in the southeastern part of the country, historically designated for Xhosa-speaking people during the apartheid era.
  • D. Ciskei
    Ciskei was a nominally independent Bantustan in southeastern South Africa established under apartheid as a homeland for Xhosa-speaking people.
  • E. Kwaluseni
    Kwaluseni is a town in Eswatini known primarily as the main campus site of the University of Eswatini.
  • 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc1fd5d48190a56981cee95ebd69 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:50 p.m.