Triple

T127445
Position Surface form Disambiguated ID Type / Status
Subject Free French Forces E2579 entity
Predicate garrison P75 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: [Free French Forces, garrison, Algiers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Algiers
Context triple: [Free French Forces, garrison, 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a25761e9248190a7205bfc36cb5c45 completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a305e1600c81909e421bf423229878 completed Feb. 28, 2026, 3:12 p.m.
Created at: Feb. 28, 2026, 2:30 a.m.