Triple

T1871289
Position Surface form Disambiguated ID Type / Status
Subject Borkou-Ennedi-Tibesti E39039 entity
Predicate namedAfter P63 FINISHED
Object Ennedi
Ennedi is a remote region in northeastern Chad renowned for its dramatic sandstone massifs, rock arches, and prehistoric rock art.
 E227593 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: Ennedi | Statement: [Borkou-Ennedi-Tibesti, namedAfter, Ennedi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ennedi
Context triple: [Borkou-Ennedi-Tibesti, namedAfter, Ennedi]
  • A. Wele-Nzas
    Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Ewondo
    Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
  • D. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • E. Kié-Ntem
    Kié-Ntem is a province in mainland Equatorial Guinea known for its largely forested landscapes and border location with Cameroon and Gabon.
  • 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: Ennedi
Triple: [Borkou-Ennedi-Tibesti, namedAfter, Ennedi]
Generated description
Ennedi is a remote region in northeastern Chad renowned for its dramatic sandstone massifs, rock arches, and prehistoric rock art.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ennedi
Target entity description: Ennedi is a remote region in northeastern Chad renowned for its dramatic sandstone massifs, rock arches, and prehistoric rock art.
  • A. Wele-Nzas
    Wele-Nzas is a province in mainland Equatorial Guinea known for its forests, border location near Gabon and Cameroon, and the city of Mongomo.
  • B. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • C. Ewondo
    Ewondo is a Bantu language spoken primarily by the Ewondo people in central Cameroon, including in and around the capital city, Yaoundé.
  • D. Maroua
    Maroua is a prominent city in northern Cameroon known as a regional commercial and cultural center near the Sahel.
  • E. Kié-Ntem
    Kié-Ntem is a province in mainland Equatorial Guinea known for its largely forested landscapes and border location with Cameroon and Gabon.
  • 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_69a8862f7074819096afe7fe65e179e9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0ba90e08190b990875d6e8e7e4a completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fcb534881908415237d24b4d8b9 completed March 9, 2026, 1:18 a.m.
NEDg Description generation batch_69ae204fe6148190915219beb27128bc completed March 9, 2026, 1:20 a.m.
NED2 Entity disambiguation (via description) batch_69ae20d09c748190aebbfb88f0eedbaa completed March 9, 2026, 1:22 a.m.
Created at: March 4, 2026, 7:34 p.m.