Triple

T539962
Position Surface form Disambiguated ID Type / Status
Subject Strasbourg E12607 entity
Predicate twinCity P1072 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: [Strasbourg, twinCity, Oran]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oran
Context triple: [Strasbourg, twinCity, 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. Derna
    Derna is a coastal city in eastern Libya known for its strategic location, turbulent political history, and role as a focal point in the country's conflicts.
  • E. 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.
  • 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_69a49334226c81908b0ea1689ef6aa3f completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985e51908190a34aa82ea9dbee1e completed March 1, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc5d690881908742b313f28a0012 completed March 1, 2026, 11:31 p.m.
Created at: March 1, 2026, 7:32 p.m.