Triple

T7569840
Position Surface form Disambiguated ID Type / Status
Subject Seraïdi E179210 entity
Predicate partOf P40 FINISHED
Object Annaba metropolitan area E33533 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: Annaba metropolitan area | Statement: [Seraïdi, partOf, Annaba metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Annaba metropolitan area
Context triple: [Seraïdi, partOf, Annaba metropolitan area]
  • A. Annaba chosen
    Annaba is a major port city in northeastern Algeria, known for its Mediterranean coastline, industrial activity, and historical significance.
  • B. Medeba
    Medeba is an ancient city east of the Dead Sea, known from biblical accounts and later as a significant settlement in the region of Moab.
  • C. Radès
    Radès is a coastal city in northern Tunisia known for its major sports facilities, including the national stadium that hosts prominent football clubs and international events.
  • D. Benslimane
    Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
  • 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_69c69f316e50819081a271c85c06f918 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f91ec780819099de6227a27bf5a5 completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b4ed90808190852ca09c06a3dc3d completed March 29, 2026, 5:13 a.m.
Created at: March 27, 2026, 3:51 p.m.