Triple

T3569752
Position Surface form Disambiguated ID Type / Status
Subject Canberra Airport E75538 entity
Predicate near P350 FINISHED
Object Majura
Majura is a district in the northeastern part of Canberra, Australia, known for its rural character, military training areas, and proximity to key transport infrastructure.
 E377905 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: Majura | Statement: [Canberra Airport, near, Majura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Majura
Context triple: [Canberra Airport, near, Majura]
  • A. Mudjimba
    Mudjimba is a coastal suburb on Queensland’s Sunshine Coast in Australia, known for its beaches and relaxed seaside atmosphere.
  • B. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • C. Yamba
    Yamba is a coastal town in northern New South Wales, Australia, known for its beaches, fishing, and laid-back holiday atmosphere.
  • D. Murrurundi
    Murrurundi is a small rural town in New South Wales, Australia, known for its scenic setting in the Upper Hunter region and its historic buildings.
  • E. Mooloolaba
    Mooloolaba is a popular coastal resort town in Queensland, Australia, known for its surf beaches, esplanade, and tourism-focused waterfront.
  • 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: Majura
Triple: [Canberra Airport, near, Majura]
Generated description
Majura is a district in the northeastern part of Canberra, Australia, known for its rural character, military training areas, and proximity to key transport infrastructure.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Majura
Target entity description: Majura is a district in the northeastern part of Canberra, Australia, known for its rural character, military training areas, and proximity to key transport infrastructure.
  • A. Mudjimba
    Mudjimba is a coastal suburb on Queensland’s Sunshine Coast in Australia, known for its beaches and relaxed seaside atmosphere.
  • B. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • C. Yamba
    Yamba is a coastal town in northern New South Wales, Australia, known for its beaches, fishing, and laid-back holiday atmosphere.
  • D. Murrurundi
    Murrurundi is a small rural town in New South Wales, Australia, known for its scenic setting in the Upper Hunter region and its historic buildings.
  • E. Mooloolaba
    Mooloolaba is a popular coastal resort town in Queensland, Australia, known for its surf beaches, esplanade, and tourism-focused waterfront.
  • 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_69ad85d512708190829c8b2d3a2ccfb8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0c1ecb081909051bcc1f38eea31 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48825d5a08190b57407b660fb5954 completed March 13, 2026, 9:56 p.m.
NEDg Description generation batch_69b4904097648190a26bce8da54a613f completed March 13, 2026, 10:31 p.m.
NED2 Entity disambiguation (via description) batch_69b4aefb58448190b7d34343a5dbb0f6 completed March 14, 2026, 12:42 a.m.
Created at: March 8, 2026, 3:21 p.m.