Triple

T12543149
Position Surface form Disambiguated ID Type / Status
Subject Shirak Province E299892 entity
Predicate containsVillage P4011 FINISHED
Object Vardaghbyur
Vardaghbyur is a rural village located in Armenia's Shirak Province.
E988814 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: Vardaghbyur | Statement: [Shirak Province, containsVillage, Vardaghbyur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vardaghbyur
Context triple: [Shirak Province, containsVillage, Vardaghbyur]
  • A. Garmsar
    Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
  • B. Lebesby
    Lebesby is a sparsely populated coastal municipality in Troms og Finnmark county in northern Norway, known for its Arctic landscapes, fishing communities, and proximity to the Barents Sea.
  • C. Sarnaghbyur
    Sarnaghbyur is a village in northwestern Armenia known for its location within the country’s Shirak Province.
  • D. Övdalian
    Övdalian is a North Germanic language variety spoken in the Älvdalen region of Sweden, noted for preserving many archaic features lost in standard Swedish.
  • E. Arboga
    Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
  • 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: Vardaghbyur
Triple: [Shirak Province, containsVillage, Vardaghbyur]
Generated description
Vardaghbyur is a rural village located in Armenia's Shirak Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vardaghbyur
Target entity description: Vardaghbyur is a rural village located in Armenia's Shirak Province.
  • A. Garmsar
    Garmsar is a city in Semnan Province of north-central Iran, known as a regional transport hub and gateway between Tehran and eastern parts of the country.
  • B. Lebesby
    Lebesby is a sparsely populated coastal municipality in Troms og Finnmark county in northern Norway, known for its Arctic landscapes, fishing communities, and proximity to the Barents Sea.
  • C. Sarnaghbyur chosen
    Sarnaghbyur is a village in northwestern Armenia known for its location within the country’s Shirak Province.
  • D. Övdalian
    Övdalian is a North Germanic language variety spoken in the Älvdalen region of Sweden, noted for preserving many archaic features lost in standard Swedish.
  • E. Arboga
    Arboga is a historic small town in central Sweden known for its medieval heritage and well-preserved old town.
  • 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_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_69f65eb317148190990d47f50324a1b1 completed May 2, 2026, 8:29 p.m.
NEDg Description generation batch_69f65fadc97081908376913e390cfc3d completed May 2, 2026, 8:33 p.m.
NED2 Entity disambiguation (via description) batch_69f660c3d914819097b57784889ca389 completed May 2, 2026, 8:38 p.m.
Created at: April 8, 2026, 9:57 p.m.