Triple

T2391205
Position Surface form Disambiguated ID Type / Status
Subject Lope National Park E48946 entity
Predicate nearestCity P350 FINISHED
Object Mikongo
Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
 E266554 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: Mikongo | Statement: [Lope National Park, nearestCity, Mikongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mikongo
Context triple: [Lope National Park, nearestCity, Mikongo]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. 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.
  • C. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • D. Mishongnovi
    Mishongnovi is a traditional Hopi village in northeastern Arizona, known as one of the oldest continuously inhabited settlements in North America.
  • E. Mokena
    Mokena is a suburban village in Will County, Illinois, located southwest of Chicago.
  • 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: Mikongo
Triple: [Lope National Park, nearestCity, Mikongo]
Generated description
Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mikongo
Target entity description: Mikongo is a small settlement in central Gabon that serves as a key access point for visitors exploring Lope National Park.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. 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.
  • C. Sanglechi
    Sanglechi is a lesser-known Eastern Iranian language spoken in parts of northeastern Afghanistan and adjacent regions.
  • D. Mishongnovi
    Mishongnovi is a traditional Hopi village in northeastern Arizona, known as one of the oldest continuously inhabited settlements in North America.
  • E. Mokena
    Mokena is a suburban village in Will County, Illinois, located southwest of Chicago.
  • 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_69a88aa5f63081908d07fd302029fcbd completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc87457388190822d5506327db8f2 completed March 7, 2026, 6:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf3a3a2c8190a29b8ce47e40c3f8 completed March 9, 2026, 12:38 p.m.
NEDg Description generation batch_69aec423e6608190aff6b12d31c9f533 completed March 9, 2026, 12:59 p.m.
NED2 Entity disambiguation (via description) batch_69aec570ec88819089a2afc42aec1088 completed March 9, 2026, 1:04 p.m.
Created at: March 4, 2026, 7:57 p.m.