Triple

T14176359
Position Surface form Disambiguated ID Type / Status
Subject Lower Shabelle E351341 entity
Predicate hasTown P847 FINISHED
Object Wanlaweyn
Wanlaweyn is a town in southern Somalia that serves as an important local center within the Lower Shabelle region.
E1084505 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: Wanlaweyn | Statement: [Lower Shabelle, hasTown, Wanlaweyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wanlaweyn
Context triple: [Lower Shabelle, hasTown, Wanlaweyn]
  • A. Aywaille
    Aywaille is a municipality in eastern Belgium known for its scenic Ardennes landscapes and outdoor recreation opportunities.
  • B. Wanhatti
    Wanhatti is a village in Suriname known as a Maroon settlement located within the country’s eastern Marowijne District.
  • C. Weyarn
    Weyarn is a small Bavarian municipality in southern Germany, located in the Alpine foothills and known for its historic monastery and rural character.
  • D. Hawise
    Hawise is a medieval European female given name borne by several noblewomen in England and France.
  • E. Leyhof
    Leyhof is a residential neighborhood in the Dutch town of Leiderdorp, located in the province of South Holland.
  • 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: Wanlaweyn
Triple: [Lower Shabelle, hasTown, Wanlaweyn]
Generated description
Wanlaweyn is a town in southern Somalia that serves as an important local center within the Lower Shabelle region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wanlaweyn
Target entity description: Wanlaweyn is a town in southern Somalia that serves as an important local center within the Lower Shabelle region.
  • A. Aywaille
    Aywaille is a municipality in eastern Belgium known for its scenic Ardennes landscapes and outdoor recreation opportunities.
  • B. Wanhatti
    Wanhatti is a village in Suriname known as a Maroon settlement located within the country’s eastern Marowijne District.
  • C. Weyarn
    Weyarn is a small Bavarian municipality in southern Germany, located in the Alpine foothills and known for its historic monastery and rural character.
  • D. Hawise
    Hawise is a medieval European female given name borne by several noblewomen in England and France.
  • E. Leyhof
    Leyhof is a residential neighborhood in the Dutch town of Leiderdorp, located in the province of South Holland.
  • 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61c76e8081909994b95b631100e9 completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf80cdae88190ae987b49218c281d completed May 7, 2026, 8:37 p.m.
NEDg Description generation batch_69fd067e73708190adcb4e1c2fbf210d completed May 7, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_69fd0c5161dc8190a923c5b00dc5b53a completed May 7, 2026, 10:04 p.m.
Created at: April 10, 2026, 1:02 a.m.