Triple

T654877
Position Surface form Disambiguated ID Type / Status
Subject Gweru E11624 entity
Predicate railConnectsTo P13914 FINISHED
Object Beira
Beira is a major port city in central Mozambique that serves as a key transport and trade hub for the region.
 E66877 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: Beira | Statement: [Gweru, railConnectsTo, Beira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beira
Context triple: [Gweru, railConnectsTo, Beira]
  • A. Beira
    Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
  • B. Port of Maputo
    The Port of Maputo is Mozambique’s principal deep-water seaport and a major regional hub for maritime trade in southeastern Africa.
  • C. Praia
    Praia is the capital and largest city of Cape Verde, located on the southern coast of Santiago Island in the central Atlantic Ocean.
  • D. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • E. Olinda
    Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
  • 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: Beira
Triple: [Gweru, railConnectsTo, Beira]
Generated description
Beira is a major port city in central Mozambique that serves as a key transport and trade hub for the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Beira
Target entity description: Beira is a major port city in central Mozambique that serves as a key transport and trade hub for the region.
  • A. Beira chosen
    Beira is a major port city in central Mozambique, serving as a key commercial and transport hub for the region.
  • B. Port of Maputo
    The Port of Maputo is Mozambique’s principal deep-water seaport and a major regional hub for maritime trade in southeastern Africa.
  • C. Praia
    Praia is the capital and largest city of Cape Verde, located on the southern coast of Santiago Island in the central Atlantic Ocean.
  • D. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • E. Olinda
    Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
  • F. None of above.

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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a517ac148190aa032b77885bf709 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a591486b708190b0191e958c6c8851 completed March 2, 2026, 1:31 p.m.
NEDg Description generation batch_69a592095c7881909c7bdeb5ac5a2cdd completed March 2, 2026, 1:35 p.m.
NED2 Entity disambiguation (via description) batch_69a595bf289c8190971799c6942f29e3 completed March 2, 2026, 1:50 p.m.
Created at: March 1, 2026, 7:36 p.m.