Triple

T16486495
Position Surface form Disambiguated ID Type / Status
Subject Falémé River E400457 entity
Predicate confluenceNear P8203 FINISHED
Object Kidira
Kidira is a town in eastern Senegal near the Malian border that serves as an important road and rail crossing point between the two countries.
E1216133 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: Kidira | Statement: [Falémé River, confluenceNear, Kidira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kidira
Context triple: [Falémé River, confluenceNear, Kidira]
  • A. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • B. Mubaira
    Mubaira is a small town located in the Mashonaland West Province of northern Zimbabwe.
  • C. Makeda
    "Makeda" is a popular neo-soul/R&B song by the French duo Les Nubians, known for its smooth harmonies and Afrocentric themes.
  • D. Kirsha
    Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
  • E. Adailiya
    Adailiya is a residential district in Kuwait City known for its embassies, sports facilities, and central location within the capital.
  • 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: Kidira
Triple: [Falémé River, confluenceNear, Kidira]
Generated description
Kidira is a town in eastern Senegal near the Malian border that serves as an important road and rail crossing point between the two countries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kidira
Target entity description: Kidira is a town in eastern Senegal near the Malian border that serves as an important road and rail crossing point between the two countries.
  • A. Katisha
    Katisha is a formidable, older noblewoman and comic villainess in Gilbert and Sullivan’s operetta "The Mikado," known for her dramatic presence and unrequited love for Nanki-Poo.
  • B. Mubaira
    Mubaira is a small town located in the Mashonaland West Province of northern Zimbabwe.
  • C. Makeda
    "Makeda" is a popular neo-soul/R&B song by the French duo Les Nubians, known for its smooth harmonies and Afrocentric themes.
  • D. Kirsha
    Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
  • E. Adailiya
    Adailiya is a residential district in Kuwait City known for its embassies, sports facilities, and central location within the capital.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e078d0c8190a5698a5eb9df22d4 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582275308190a0fb3944d74916cf completed May 10, 2026, 10:04 a.m.
NEDg Description generation batch_6a0058a1c51c81908f49db448a4d0365 completed May 10, 2026, 10:06 a.m.
NED2 Entity disambiguation (via description) batch_6a00595837c4819093f1a1a35185bc4b completed May 10, 2026, 10:09 a.m.
Created at: April 10, 2026, 5:13 a.m.