Triple

T1272365
Position Surface form Disambiguated ID Type / Status
Subject Niger River E15736 entity
Predicate associatedCity P3207 FINISHED
Object Timbuktu
Timbuktu is an ancient city in Mali famed as a historic center of trans-Saharan trade and Islamic scholarship.
 E144680 NE FINISHED

How this triple was built (4 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: [Niger River, associatedCity, Timbuktu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Timbuktu
Context triple: [Niger River, associatedCity, Timbuktu]
  • A. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • B. Téboursouk
    Téboursouk is a town in northern Tunisia known as a gateway to the nearby ancient Roman ruins of Dougga.
  • C. 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.
  • D. Qunu
    Qunu is a rural village in South Africa’s Eastern Cape province, best known as Nelson Mandela’s childhood home and final resting place.
  • E. Sanaa
    Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Timbuktu
Triple: [Niger River, associatedCity, Timbuktu]
Generated description
Timbuktu is an ancient city in Mali famed as a historic center of trans-Saharan trade and Islamic scholarship.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Timbuktu
Target entity description: Timbuktu is an ancient city in Mali famed as a historic center of trans-Saharan trade and Islamic scholarship.
  • A. Tanta
    Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
  • B. Téboursouk
    Téboursouk is a town in northern Tunisia known as a gateway to the nearby ancient Roman ruins of Dougga.
  • C. 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.
  • D. Qunu
    Qunu is a rural village in South Africa’s Eastern Cape province, best known as Nelson Mandela’s childhood home and final resting place.
  • E. Sanaa
    Sanaa is a table-service restaurant at Disney’s Animal Kingdom Lodge known for its African-inspired cuisine with Indian flavors and savanna views of roaming wildlife.
  • F. None of above. chosen

Provenance (5 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_69a4935a94308190bb92555b79032824 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4c06c033081909bc594157abaf5bb completed March 1, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac998e56488190ac3cf51563335e30 completed March 7, 2026, 9:33 p.m.
NEDg Description generation batch_69ac9a13e9548190ae1fbfeba3326cd5 completed March 7, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69ac9a96d4f081908e608a3f247bbfb2 completed March 7, 2026, 9:37 p.m.
Created at: March 1, 2026, 7:50 p.m.