Triple

T14110334
Position Surface form Disambiguated ID Type / Status
Subject Marcory E339617 entity
Predicate adjacentTo P224 FINISHED
Object Koumassi
Koumassi is a populous urban commune and district of Abidjan in Côte d'Ivoire, known for its dense residential neighborhoods and commercial activity.
E1079543 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: Koumassi | Statement: [Marcory, adjacentTo, Koumassi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koumassi
Context triple: [Marcory, adjacentTo, Koumassi]
  • A. Fougamou
    Fougamou is a small town in southwestern Gabon that serves as an administrative and transport hub in Ngounié Province.
  • B. Ekondo-Titi
    Ekondo-Titi is a coastal town and commune in Cameroon's Southwest Region, known for its agricultural activities and location near the Ndian River and the Atlantic coast.
  • C. Duékoué
    Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
  • D. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • E. Ebolowa
    Ebolowa is a city in southern Cameroon that serves as an administrative and commercial center for the surrounding agricultural region.
  • 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: Koumassi
Triple: [Marcory, adjacentTo, Koumassi]
Generated description
Koumassi is a populous urban commune and district of Abidjan in Côte d'Ivoire, known for its dense residential neighborhoods and commercial activity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Koumassi
Target entity description: Koumassi is a populous urban commune and district of Abidjan in Côte d'Ivoire, known for its dense residential neighborhoods and commercial activity.
  • A. Fougamou
    Fougamou is a small town in southwestern Gabon that serves as an administrative and transport hub in Ngounié Province.
  • B. Ekondo-Titi
    Ekondo-Titi is a coastal town and commune in Cameroon's Southwest Region, known for its agricultural activities and location near the Ndian River and the Atlantic coast.
  • C. Duékoué
    Duékoué is a town in western Côte d'Ivoire that became notorious as a major site of violence and massacres during the country's civil conflicts.
  • D. Benina
    Benina is a town in eastern Libya that serves as the main gateway to the nearby city of Benghazi through its international airport.
  • E. Ebolowa
    Ebolowa is a city in southern Cameroon that serves as an administrative and commercial center for the surrounding agricultural region.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600e6a688190a1243a30ae9b7157 completed April 14, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b699108190993f1102418ecff1 completed May 7, 2026, 5:49 p.m.
NEDg Description generation batch_69fcd2d99c4c8190baf15d470ead7b1c completed May 7, 2026, 5:58 p.m.
NED2 Entity disambiguation (via description) batch_69fcd3853e848190a210d1c8c08bd6cc completed May 7, 2026, 6:01 p.m.
Created at: April 9, 2026, 10:22 p.m.