Triple

T7078614
Position Surface form Disambiguated ID Type / Status
Subject Tosk region E164886 entity
Predicate hasCity P316 FINISHED
Object Lushnjë
Lushnjë is a city in central Albania known for its agricultural importance and role in the country’s political history.
 E650279 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: Lushnjë | Statement: [Tosk region, hasCity, Lushnjë]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lushnjë
Context triple: [Tosk region, hasCity, Lushnjë]
  • A. Peshkopi
    Peshkopi is a small town in northeastern Albania known as a regional center near the border with North Macedonia and the Korab mountain range.
  • B. Elbasan
    Elbasan is a city in central Albania known as an important industrial and transportation hub with historical roots dating back to the Ottoman era.
  • C. Kavajë
    Kavajë is a city in western Albania known for its historical role in the country’s independence movement and its proximity to the Adriatic coast.
  • D. Korçë
    Korçë is a city in southeastern Albania known as a cultural and educational center with rich Orthodox Christian heritage and historic architecture.
  • E. Gjirokastër
    Gjirokastër is a historic stone-built city in southern Albania, recognized as a UNESCO World Heritage Site for its well-preserved Ottoman-era architecture.
  • 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: Lushnjë
Triple: [Tosk region, hasCity, Lushnjë]
Generated description
Lushnjë is a city in central Albania known for its agricultural importance and role in the country’s political history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lushnjë
Target entity description: Lushnjë is a city in central Albania known for its agricultural importance and role in the country’s political history.
  • A. Peshkopi
    Peshkopi is a small town in northeastern Albania known as a regional center near the border with North Macedonia and the Korab mountain range.
  • B. Elbasan
    Elbasan is a city in central Albania known as an important industrial and transportation hub with historical roots dating back to the Ottoman era.
  • C. Kavajë
    Kavajë is a city in western Albania known for its historical role in the country’s independence movement and its proximity to the Adriatic coast.
  • D. Korçë
    Korçë is a city in southeastern Albania known as a cultural and educational center with rich Orthodox Christian heritage and historic architecture.
  • E. Gjirokastër
    Gjirokastër is a historic stone-built city in southern Albania, recognized as a UNESCO World Heritage Site for its well-preserved Ottoman-era architecture.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4ef47d48190b31125d1b57f7bec completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cbc74dac8190993f613d8219fa8d completed March 28, 2026, 12:38 p.m.
NEDg Description generation batch_69c7cc5af4f48190a146f7026307bfbe completed March 28, 2026, 12:40 p.m.
NED2 Entity disambiguation (via description) batch_69c7cd0eb36c8190bc8e4265033d214f completed March 28, 2026, 12:43 p.m.
Created at: March 27, 2026, 2:40 p.m.