Triple

T2899739
Position Surface form Disambiguated ID Type / Status
Subject Houari Boumediene Airport E62626 entity
Predicate servesCity P82 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: [Houari Boumediene Airport, servesCity, Algiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers
Context triple: [Houari Boumediene Airport, servesCity, 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. 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.
  • D. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • E. Tripoli
    Tripoli is a historic city in the central Peloponnese of Greece that serves as the main urban and administrative center of the Arcadia region.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0ad7bbc8190822738baa6935b74 completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1f859f698819087f4ac614071d41f completed March 11, 2026, 11:18 p.m.
Created at: March 6, 2026, 10:10 p.m.