Triple

T6404953
Position Surface form Disambiguated ID Type / Status
Subject Mémoires de guerre E144155 entity
Predicate setting P1957 FINISHED
Object Algiers 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 | Statement: [Mémoires de guerre, setting, Algiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers
Context triple: [Mémoires de guerre, setting, Algiers]
  • 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. Tunis
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • C. Berrechid
    Berrechid is a rapidly growing city in northwestern Morocco known as an important agricultural and industrial hub within the Casablanca-Settat region.
  • D. Benslimane
    Benslimane is a town and provincial capital in northwestern Morocco, known for its forests and proximity to Casablanca.
  • E. Beni Mellal
    Beni Mellal is a major city in central Morocco known for its agricultural importance and its location at the foot of the Middle Atlas mountains.
  • 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_69c008dc56fc81908d43ffcc11d73bdd completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c068b0950c819091169aa1a3be0e88 completed March 22, 2026, 10:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6386f361c819098dbe01b0cb07b06 completed March 27, 2026, 7:57 a.m.
Created at: March 22, 2026, 4:35 p.m.