Triple

T3053869
Position Surface form Disambiguated ID Type / Status
Subject Maiduguri E60433 entity
Predicate roadConnection P385 FINISHED
Object Monguno
Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
 E321867 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: Monguno | Statement: [Maiduguri, roadConnection, Monguno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Monguno
Context triple: [Maiduguri, roadConnection, Monguno]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Nzega
    Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
  • C. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • D. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • E. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • 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: Monguno
Triple: [Maiduguri, roadConnection, Monguno]
Generated description
Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Monguno
Target entity description: Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Nzega
    Nzega is a town and district in western Tanzania that serves as an important commercial and transport hub within the Tabora Region.
  • C. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • D. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • E. Mikongo
    Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • 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_69ad8578137c81908259dcb27c7d6d7c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ad9bf51b5081908ce355a76cfa9e3c completed March 8, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef00630c8190a3b5b2854350ecb9 completed March 11, 2026, 10:38 p.m.
NEDg Description generation batch_69b1efa8c11081908661b33e465e11bc completed March 11, 2026, 10:41 p.m.
NED2 Entity disambiguation (via description) batch_69b1f062abf48190ab891463c5b33622 completed March 11, 2026, 10:44 p.m.
Created at: March 8, 2026, 3:01 p.m.