Triple

T12543079
Position Surface form Disambiguated ID Type / Status
Subject Lori Province E299890 entity
Predicate hasTown P847 FINISHED
Object Stepanavan
Stepanavan is a town in northern Armenia known for its cool climate, surrounding forests, and proximity to the Stepanavan Dendropark botanical garden.
 E988812 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: Stepanavan | Statement: [Lori Province, hasTown, Stepanavan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stepanavan
Context triple: [Lori Province, hasTown, Stepanavan]
  • A. Stalinets
    Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
  • B. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • C. Shostka
    Shostka is a city in northern Ukraine’s Sumy Oblast, historically known as an important center of the chemical and munitions industry.
  • D. Sventsiany
    Sventsiany is a historical town in present-day Lithuania, known in Polish as Święciany and associated with the multicultural heritage of the former Grand Duchy of Lithuania.
  • E. Novoslobodskaya
    Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
  • 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: Stepanavan
Triple: [Lori Province, hasTown, Stepanavan]
Generated description
Stepanavan is a town in northern Armenia known for its cool climate, surrounding forests, and proximity to the Stepanavan Dendropark botanical garden.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stepanavan
Target entity description: Stepanavan is a town in northern Armenia known for its cool climate, surrounding forests, and proximity to the Stepanavan Dendropark botanical garden.
  • A. Stalinets
    Stalinets was the former name of the Russian football club now known as Lokomotiv Moscow.
  • B. Kirovakan
    Kirovakan is the former name of Vanadzor, a major industrial city in northern Armenia.
  • C. Shostka
    Shostka is a city in northern Ukraine’s Sumy Oblast, historically known as an important center of the chemical and munitions industry.
  • D. Sventsiany
    Sventsiany is a historical town in present-day Lithuania, known in Polish as Święciany and associated with the multicultural heritage of the former Grand Duchy of Lithuania.
  • E. Novoslobodskaya
    Novoslobodskaya is a Moscow Metro station famed for its distinctive stained-glass panels and ornate, cathedral-like interior design.
  • 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_69d6ada707008190aaec1238117c9379 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9547d6df4819080db8415d386ed38 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6557e6d4c81909ed54a039e92a160 completed May 2, 2026, 7:50 p.m.
NEDg Description generation batch_69f6566f40c08190baec227fb660c948 completed May 2, 2026, 7:54 p.m.
NED2 Entity disambiguation (via description) batch_69f657aec8fc8190b3b08ccb95595958 completed May 2, 2026, 7:59 p.m.
Created at: April 8, 2026, 9:57 p.m.