Triple

T8529931
Position Surface form Disambiguated ID Type / Status
Subject Fathi Arafat E201917 entity
Predicate workLocation P7 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: [Fathi Arafat, workLocation, Tunis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tunis
Context triple: [Fathi Arafat, workLocation, 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe67409f08190b20d13d26e9a362c completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce890333d08190b510d970e6d6fee5 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:17 p.m.