Triple

T1813167
Position Surface form Disambiguated ID Type / Status
Subject Mali E40373 entity
Predicate containsCity P294 FINISHED
Object Timbuktu E144680 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: Timbuktu | Statement: [Mali, containsCity, Timbuktu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Timbuktu
Context triple: [Mali, containsCity, Timbuktu]
  • A. Timbuktu chosen
    Timbuktu is an ancient city in Mali famed as a historic center of trans-Saharan trade and Islamic scholarship.
  • B. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • C. Téboursouk
    Téboursouk is a town in northern Tunisia known as a gateway to the nearby ancient Roman ruins of Dougga.
  • D. Umm al-Kitab
    Umm al-Kitab is an honorific title for Surah Al-Fatiha, emphasizing its foundational status as the opening and central chapter of the Qur’an.
  • E. Gash‑Barka
    Gash‑Barka is a largely agricultural region in southwestern Eritrea known for its fertile land and role as one of the country’s main food-producing areas.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa65c775408190b4f5912786720e28 completed March 6, 2026, 5:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5e5142c8190bc90da38b02e95e2 completed March 8, 2026, 5:46 p.m.
Created at: March 4, 2026, 7:32 p.m.