Triple

T14380304
Position Surface form Disambiguated ID Type / Status
Subject Kebbi Kingdom E356582 entity
Predicate capital P234 FINISHED
Object Surame
Surame is a historic town in northwestern Nigeria that once served as the political and administrative center of the Kebbi Kingdom.
E1096103 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: Surame | Statement: [Kebbi Kingdom, capital, Surame]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surame
Context triple: [Kebbi Kingdom, capital, Surame]
  • A. Asakura
    Asakura is a city in Fukuoka Prefecture, Japan, known for its rural landscapes, historic sites, and agricultural products such as fruits and vegetables.
  • B. Go (surname)
    Go is an East Asian surname, commonly associated with Korean and Chinese lineages and represented by various characters and romanizations.
  • C. Nakayama family
    The Nakayama family is a Japanese lineage historically known for its connections to the imperial court and for producing notable figures in Japan’s political and cultural life.
  • D. Saito
    Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
  • E. Shiranesansō
    Shiranesansō is a mountain hut located on or near Mount Kita in Japan, serving as accommodation and a base for hikers and climbers in the Southern Japanese Alps.
  • 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: Surame
Triple: [Kebbi Kingdom, capital, Surame]
Generated description
Surame is a historic town in northwestern Nigeria that once served as the political and administrative center of the Kebbi Kingdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Surame
Target entity description: Surame is a historic town in northwestern Nigeria that once served as the political and administrative center of the Kebbi Kingdom.
  • A. Asakura
    Asakura is a city in Fukuoka Prefecture, Japan, known for its rural landscapes, historic sites, and agricultural products such as fruits and vegetables.
  • B. Go (surname)
    Go is an East Asian surname, commonly associated with Korean and Chinese lineages and represented by various characters and romanizations.
  • C. Nakayama family
    The Nakayama family is a Japanese lineage historically known for its connections to the imperial court and for producing notable figures in Japan’s political and cultural life.
  • D. Saito
    Saito is a Japanese surname commonly borne by notable figures in fields such as politics, sports, and the arts.
  • E. Shiranesansō
    Shiranesansō is a mountain hut located on or near Mount Kita in Japan, serving as accommodation and a base for hikers and climbers in the Southern Japanese Alps.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900bbfb08190a1e56f281a2374c0 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c590660819090652e75418f2747 completed May 8, 2026, 2:37 a.m.
NEDg Description generation batch_69fd4e4bae188190a8d1c5b833d58cd8 completed May 8, 2026, 2:45 a.m.
NED2 Entity disambiguation (via description) batch_69fd4f5782b4819081d32dbef032ac61 completed May 8, 2026, 2:49 a.m.
Created at: April 10, 2026, 1:16 a.m.