Triple

T14224227
Position Surface form Disambiguated ID Type / Status
Subject Cayor E352575 entity
Predicate capital P234 FINISHED
Object Kebemer
Kebemer is a town in northwestern Senegal that historically served as an important administrative center in the former Wolof kingdom of Cayor.
 E1087183 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: Kebemer | Statement: [Cayor, capital, Kebemer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kebemer
Context triple: [Cayor, capital, Kebemer]
  • A. Kenberma
    Kenberma is a coastal village neighborhood within the town of Hull, Massachusetts, known for its residential community and proximity to Nantasket Beach.
  • B. Kaleibar
    Kaleibar is a small historic city in northwestern Iran known for its mountainous landscapes and proximity to the Babak Castle fortress.
  • C. Sebkay
    Sebkay was an obscure and possibly short-reigning pharaoh of Egypt’s 13th Dynasty during the Second Intermediate Period.
  • D. Zemba
    Zemba is a Bantu language variety spoken primarily in southwestern Angola and northern Namibia, closely related to and often considered a dialect of Herero.
  • E. Kangaba
    Kangaba is a historic town in southwestern Mali, traditionally regarded as an early political and cultural center of the Mali Empire and the Keita dynasty.
  • 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: Kebemer
Triple: [Cayor, capital, Kebemer]
Generated description
Kebemer is a town in northwestern Senegal that historically served as an important administrative center in the former Wolof kingdom of Cayor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kebemer
Target entity description: Kebemer is a town in northwestern Senegal that historically served as an important administrative center in the former Wolof kingdom of Cayor.
  • A. Kenberma
    Kenberma is a coastal village neighborhood within the town of Hull, Massachusetts, known for its residential community and proximity to Nantasket Beach.
  • B. Kaleibar
    Kaleibar is a small historic city in northwestern Iran known for its mountainous landscapes and proximity to the Babak Castle fortress.
  • C. Sebkay
    Sebkay was an obscure and possibly short-reigning pharaoh of Egypt’s 13th Dynasty during the Second Intermediate Period.
  • D. Zemba
    Zemba is a Bantu language variety spoken primarily in southwestern Angola and northern Namibia, closely related to and often considered a dialect of Herero.
  • E. Kangaba
    Kangaba is a historic town in southwestern Mali, traditionally regarded as an early political and cultural center of the Mali Empire and the Keita dynasty.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6227c288819081473ce44f9f0934 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd281611b48190b787e38ba9c733a4 completed May 8, 2026, 12:02 a.m.
NEDg Description generation batch_69fd2a5c80308190868967a402c5fa42 completed May 8, 2026, 12:12 a.m.
NED2 Entity disambiguation (via description) batch_69fd2af4ddf8819089435b849415b941 completed May 8, 2026, 12:14 a.m.
Created at: April 10, 2026, 1:06 a.m.