Triple

T15490058
Position Surface form Disambiguated ID Type / Status
Subject Pool Department E378657 entity
Predicate containsTown P847 FINISHED
Object Mindouli
Mindouli is a town in the Republic of the Congo known as an administrative and transport hub in the Pool Department near the border with the Democratic Republic of the Congo.
 E1160828 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: Mindouli | Statement: [Pool Department, containsTown, Mindouli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mindouli
Context triple: [Pool Department, containsTown, Mindouli]
  • A. Moindou
    Moindou is a small rural commune in the South Province of New Caledonia, known for its agricultural activities and historic penal colony sites.
  • B. Monduli
    Monduli is a town in northern Tanzania that serves as the administrative center of Monduli District in the Arusha Region.
  • C. Moukari
    Moukari is a Finnish amateur radio callsign holder, identified by the callsign K9FIN Moukari.
  • D. Morungaba
    Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
  • E. Thazi
    Thazi is a town in Myanmar’s Mandalay Region that serves as a local transport and railway junction near Meiktila.
  • 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: Mindouli
Triple: [Pool Department, containsTown, Mindouli]
Generated description
Mindouli is a town in the Republic of the Congo known as an administrative and transport hub in the Pool Department near the border with the Democratic Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mindouli
Target entity description: Mindouli is a town in the Republic of the Congo known as an administrative and transport hub in the Pool Department near the border with the Democratic Republic of the Congo.
  • A. Moindou
    Moindou is a small rural commune in the South Province of New Caledonia, known for its agricultural activities and historic penal colony sites.
  • B. Monduli
    Monduli is a town in northern Tanzania that serves as the administrative center of Monduli District in the Arusha Region.
  • C. Moukari
    Moukari is a Finnish amateur radio callsign holder, identified by the callsign K9FIN Moukari.
  • D. Morungaba
    Morungaba is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and integration into the economically significant Campinas metropolitan area.
  • E. Thazi
    Thazi is a town in Myanmar’s Mandalay Region that serves as a local transport and railway junction near Meiktila.
  • 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_69d85cd53a7c819080f5b9042c4c199e completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03fac2af88190ac1d119e6b21dbe0 completed April 16, 2026, 1:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff365f27c48190822254b6da504d3d completed May 9, 2026, 1:27 p.m.
NEDg Description generation batch_69ff375856448190a61979dfff751f06 completed May 9, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69ff382f1bbc8190810d0d825430f9ea completed May 9, 2026, 1:35 p.m.
Created at: April 10, 2026, 3:48 a.m.