Triple

T245816
Position Surface form Disambiguated ID Type / Status
Subject Algeria E5033 entity
Predicate majorCity P316 FINISHED
Object Oran E19574 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: Oran | Statement: [Algeria, majorCity, Oran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oran
Context triple: [Algeria, majorCity, Oran]
  • A. Oran chosen
    Oran is a major port city on Algeria’s Mediterranean coast, known for its historical significance, vibrant culture, and role as an important economic center.
  • B. Algiers
    Algiers is the capital and largest city of Algeria, a major political, economic, and cultural center on the Mediterranean coast of North Africa.
  • 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. Misrata
    Misrata is a key coastal city in northwestern Libya, known as an important commercial and industrial hub and a strategic port on the Mediterranean Sea.
  • E. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • 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_69a379552ca081908b2c6043714f7042 completed Feb. 28, 2026, 11:25 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.