Triple

T1856860
Position Surface form Disambiguated ID Type / Status
Subject Brunswick E41721 entity
Predicate twinCity P1072 FINISHED
Object Sousse E132805 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: Sousse | Statement: [Brunswick, twinCity, Sousse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sousse
Context triple: [Brunswick, twinCity, Sousse]
  • A. Sousse chosen
    Sousse is a major coastal city in eastern Tunisia known for its historic medina, tourism, and role in the country’s modern political events.
  • B. Sfax
    Sfax is a major port city on Tunisia’s eastern coast, known as an economic hub and a significant center of political activism during the Tunisian Revolution.
  • C. Mahdia
    Mahdia is a historic coastal city in present-day Tunisia that served as the first capital of the Fatimid Caliphate and an important Mediterranean trading and naval center.
  • D. Tunis
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • E. Beni Mellal
    Beni Mellal is a major city in central Morocco known for its agricultural importance and its location at the foot of the Middle Atlas mountains.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb07fc5f08190a195a2f24d7b858a completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaddc9188190bd49d6605fd0e812 completed March 8, 2026, 9:32 p.m.
Created at: March 4, 2026, 7:33 p.m.