Triple

T10294507
Position Surface form Disambiguated ID Type / Status
Subject Loja E241447 entity
Predicate administrativeDivision P747 FINISHED
Object Loja Canton
Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
E855928 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: Loja Canton | Statement: [Loja, administrativeDivision, Loja Canton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loja Canton
Context triple: [Loja, administrativeDivision, Loja Canton]
  • A. Daguan
    Daguan was a Chinese imperial era name used during the reign of Emperor Huizong of the Song dynasty.
  • B. Zao Town
    Zao Town is a rural Japanese town known for its hot springs, ski resorts, and scenic volcanic landscapes in northeastern Honshu.
  • C. Butuan City
    Butuan City is a highly urbanized and historically significant city in the Caraga region of Mindanao in the Philippines, known as a commercial hub and an important archaeological and cultural center.
  • D. Pujiang Town
    Pujiang Town is a suburban township in Shanghai, China, known for its residential communities and connectivity via the Pujiang Line of the city’s metro system.
  • E. Xinzhuang
    Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
  • 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: Loja Canton
Triple: [Loja, administrativeDivision, Loja Canton]
Generated description
Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Loja Canton
Target entity description: Loja Canton is an administrative subdivision in southern Ecuador that encompasses the city of Loja and its surrounding areas.
  • A. Daguan
    Daguan was a Chinese imperial era name used during the reign of Emperor Huizong of the Song dynasty.
  • B. Zao Town
    Zao Town is a rural Japanese town known for its hot springs, ski resorts, and scenic volcanic landscapes in northeastern Honshu.
  • C. Butuan City
    Butuan City is a highly urbanized and historically significant city in the Caraga region of Mindanao in the Philippines, known as a commercial hub and an important archaeological and cultural center.
  • D. Pujiang Town
    Pujiang Town is a suburban township in Shanghai, China, known for its residential communities and connectivity via the Pujiang Line of the city’s metro system.
  • E. Xinzhuang
    Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
  • 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_69d381aaafc08190af475ef58dc16aba completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2d5e0f88190be3e23ba2511a1e9 completed April 7, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71d1c180481909ca9983e14cbb931 completed April 9, 2026, 3:29 a.m.
NEDg Description generation batch_69d73182d7548190ac15093aa7001db7 completed April 9, 2026, 4:56 a.m.
NED2 Entity disambiguation (via description) batch_69d7336c06308190ac72154134a26842 completed April 9, 2026, 5:04 a.m.
Created at: April 6, 2026, 11:42 a.m.