Triple

T12871378
Position Surface form Disambiguated ID Type / Status
Subject Northern Algeria E307856 entity
Predicate contains P35 FINISHED
Object Algiers metropolitan area E10377 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: Algiers metropolitan area | Statement: [Northern Algeria, contains, Algiers metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers metropolitan area
Context triple: [Northern Algeria, contains, Algiers metropolitan area]
  • A. Algiers chosen
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • B. Aïn M’lila
    Aïn M’lila is a city in northeastern Algeria known as a regional commercial and transportation hub.
  • C. Tunis
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • D. Benslimane
    Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
  • E. Mostaganem
    Mostaganem is a coastal city in northwestern Algeria known historically as a strategic Mediterranean port and regional center of trade and culture.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970905784819091631161a9de98c5 completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8ccee708190bb4caa604386e3a3 completed May 3, 2026, 2:54 a.m.
Created at: April 9, 2026, 5:38 p.m.