Triple

T10617267
Position Surface form Disambiguated ID Type / Status
Subject Manuel Magri E276152 entity
Predicate placeOfDeath P21 FINISHED
Object Tunis E11662 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: Tunis | Statement: [Manuel Magri, placeOfDeath, Tunis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tunis
Context triple: [Manuel Magri, placeOfDeath, Tunis]
  • A. Tunis chosen
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • B. 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.
  • C. 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.
  • D. Algiers
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • E. Sousse
    Sousse is a major coastal city in eastern Tunisia known for its historic medina, tourism, and role in the country’s modern political events.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df6e2df4819099a19b59d90d0dd1 completed April 8, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b7bb7108190b0f1cbe4117abec0 completed April 10, 2026, 9:28 p.m.
Created at: April 8, 2026, 7:33 p.m.