Triple

T5927622
Position Surface form Disambiguated ID Type / Status
Subject Sfax E131851 entity
Predicate hasTwinTown P919 FINISHED
Object Oran E19574 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: Oran | Statement: [Sfax, hasTwinTown, Oran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oran
Context triple: [Sfax, hasTwinTown, Oran]
  • A. Oran chosen
    Oran is a major port city on Algeria’s Mediterranean coast, known for its historical significance, vibrant culture, and role as an important economic center.
  • B. Oran Province
    Oran Province is an administrative region in northwestern Algeria centered on the coastal city of Oran, a major economic and cultural hub on the Mediterranean.
  • C. Algiers
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • D. Beji
    Beji is the given name of Beji Caid Essebsi, the Tunisian politician who served as president of Tunisia after the 2011 revolution.
  • E. Jijel Province
    Jijel Province is a coastal region in northeastern Algeria known for its Mediterranean shoreline, mountainous Kabyle-influenced hinterland, and rich natural landscapes.
  • 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_69c0085b75e88190a632f9691f9da48b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0385592b48190a885efb9549d88c7 completed March 22, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c05460c481908f3efde19e3ffa2a completed March 23, 2026, 4:23 a.m.
Created at: March 22, 2026, 4 p.m.