Triple

T6561932
Position Surface form Disambiguated ID Type / Status
Subject Kongo Central Province E153802 entity
Predicate hasTown P847 FINISHED
Object Tshela
Tshela is a town in the western Democratic Republic of the Congo, situated in the forested interior of Kongo Central Province near the border with the Republic of the Congo.
E602981 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: Tshela | Statement: [Kongo Central Province, hasTown, Tshela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tshela
Context triple: [Kongo Central Province, hasTown, Tshela]
  • A. Tsholotsho
    Tsholotsho is a rural district and township in western Zimbabwe known for its proximity to Hwange National Park and its predominantly Ndebele-speaking communities.
  • B. Gavinana
    Gavinana is a residential district in the southeastern part of Florence, Italy, known for its modern urban layout and proximity to the Arno River.
  • C. Sihawa
    Sihawa is a village in Chhattisgarh, India, known as the origin point of the Mahanadi River.
  • D. Hlengwe
    Hlengwe is a regional dialect of the Tsonga language spoken by Tsonga communities in parts of southern Africa.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • 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: Tshela
Triple: [Kongo Central Province, hasTown, Tshela]
Generated description
Tshela is a town in the western Democratic Republic of the Congo, situated in the forested interior of Kongo Central Province near the border with the Republic of the Congo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tshela
Target entity description: Tshela is a town in the western Democratic Republic of the Congo, situated in the forested interior of Kongo Central Province near the border with the Republic of the Congo.
  • A. Tsholotsho
    Tsholotsho is a rural district and township in western Zimbabwe known for its proximity to Hwange National Park and its predominantly Ndebele-speaking communities.
  • B. Gavinana
    Gavinana is a residential district in the southeastern part of Florence, Italy, known for its modern urban layout and proximity to the Arno River.
  • C. Sihawa
    Sihawa is a village in Chhattisgarh, India, known as the origin point of the Mahanadi River.
  • D. Hlengwe
    Hlengwe is a regional dialect of the Tsonga language spoken by Tsonga communities in parts of southern Africa.
  • E. Omaruru
    Omaruru is a small historic town in central Namibia known for its colonial-era architecture, vineyards, and role as a local trading and farming center.
  • 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_69c6880cb35881909b763eb0125236b9 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae38e94081908f964d130f9147d8 completed March 27, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d55fa1bc81908f2929e835051532 completed March 27, 2026, 7:07 p.m.
NEDg Description generation batch_69c6d676e43081909bf2a9cceff0b9b3 completed March 27, 2026, 7:11 p.m.
NED2 Entity disambiguation (via description) batch_69c6d843bad081909ebb887f32ea4195 completed March 27, 2026, 7:19 p.m.
Created at: March 27, 2026, 1:52 p.m.