Triple

T245772
Position Surface form Disambiguated ID Type / Status
Subject Algeria E5033 entity
Predicate largestCity P235 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: [Algeria, largestCity, Algiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers
Context triple: [Algeria, largestCity, 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. 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.
  • E. Kairouan
    Kairouan is an ancient Islamic city in central Tunisia renowned for its historic mosques, traditional architecture, and status as a major center of early Muslim scholarship and pilgrimage.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a25d128c0081909908825b302ae635 completed Feb. 28, 2026, 3:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69a3765be530819088d680acc6a26a4a completed Feb. 28, 2026, 11:12 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.