Triple

T151441
Position Surface form Disambiguated ID Type / Status
Subject Ottoman Empire E3438 entity
Predicate importantPort P2994 FINISHED
Object Tunis E11662 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: Tunis | Statement: [Ottoman Empire, importantPort, Tunis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tunis
Context triple: [Ottoman Empire, importantPort, Tunis]
  • A. Tunis chosen
    Tunis is the capital and largest city of Tunisia, serving as a major political, economic, and cultural center in the Arab world.
  • 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. 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.
  • D. Tripoli
    Tripoli is a historic Mediterranean port city that serves as the capital and largest urban center of Libya.
  • 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_69a252868de4819080e21c9938bfe8b6 completed Feb. 28, 2026, 2:27 a.m.
NER Named-entity recognition batch_69a25bab43608190ba5ebfbee6b5b6e4 completed Feb. 28, 2026, 3:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69a338e55004819096a8cc1bfec7a225 completed Feb. 28, 2026, 6:50 p.m.
Created at: Feb. 28, 2026, 2:31 a.m.