Triple

T757119
Position Surface form Disambiguated ID Type / Status
Subject French North Africa E15580 entity
Predicate administrativeCenter P1474 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: [French North Africa, administrativeCenter, Algiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers
Context triple: [French North Africa, administrativeCenter, 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. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • D. Tripoli
    Tripoli is Lebanon’s second-largest city, a historic Mediterranean port known for its medieval Mamluk architecture and vibrant commercial life.
  • E. Rabat
    Rabat is the capital city of Morocco, located on the Atlantic coast and known for its historic medina, coastal fortifications, and role as a political and administrative 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_69a493599a0081908da65f3407af1ef2 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a66ab4608190afcd81e6606c5116 completed March 1, 2026, 8:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a6891da56c8190965745d6ca13c75b completed March 3, 2026, 7:09 a.m.
Created at: March 1, 2026, 7:37 p.m.