Triple

T829002
Position Surface form Disambiguated ID Type / Status
Subject Tunisair E17920 entity
Predicate servesCity P82 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: [Tunisair, servesCity, Tunis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tunis
Context triple: [Tunisair, servesCity, 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. Algiers
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • C. Sidi Bouzid
    Sidi Bouzid is a town in central Tunisia known as the birthplace of the Arab Spring uprisings that began in late 2010.
  • D. Kairouan
    Kairouan is an ancient Islamic city in central Tunisia renowned for its historic mosques, traditional architecture, and status as a major center of early Muslim scholarship and pilgrimage.
  • E. Tunis Governorate
    Tunis Governorate is an administrative region in northeastern Tunisia that encompasses the nation’s capital city, Tunis, and serves as its political and economic center.
  • 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_69a4937c9c188190aaa216f6b466f452 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ab9b458881909aa23f0eb7cbc87f completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7edfcb7a88190b3670c6ef2b93609 completed March 4, 2026, 8:31 a.m.
Created at: March 1, 2026, 7:38 p.m.