Triple

T14897754
Position Surface form Disambiguated ID Type / Status
Subject Volkovysk E359922 entity
Predicate hasAlternativeName P39 FINISHED
Object Vawkavysk
Vawkavysk is a historic town in western Belarus known for its ancient settlement sites and role as a regional administrative and cultural center.
E1125215 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: Vawkavysk | Statement: [Volkovysk, hasAlternativeName, Vawkavysk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vawkavysk
Context triple: [Volkovysk, hasAlternativeName, Vawkavysk]
  • A. Valdosta
    Valdosta is a city in southern Georgia known as a regional commercial hub and home to Valdosta State University.
  • B. Tusten, New York
    Tusten, New York is a small rural town in Sullivan County known for its scenic Delaware River setting and outdoor recreation.
  • C. Harrisena, New York
    Harrisena, New York is a small hamlet within the town of Queensbury in Warren County, known for its rural character in the Adirondack region.
  • D. Valhalla, New York
    Valhalla, New York is a hamlet in the town of Mount Pleasant in Westchester County, known for its suburban character and several notable cemeteries and memorial sites.
  • E. Rensselaer
    Rensselaer is a masculine given name of English origin, now rare, that has historically appeared in the United States.
  • 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: Vawkavysk
Triple: [Volkovysk, hasAlternativeName, Vawkavysk]
Generated description
Vawkavysk is a historic town in western Belarus known for its ancient settlement sites and role as a regional administrative and cultural center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vawkavysk
Target entity description: Vawkavysk is a historic town in western Belarus known for its ancient settlement sites and role as a regional administrative and cultural center.
  • A. Valdosta
    Valdosta is a city in southern Georgia known as a regional commercial hub and home to Valdosta State University.
  • B. Tusten, New York
    Tusten, New York is a small rural town in Sullivan County known for its scenic Delaware River setting and outdoor recreation.
  • C. Harrisena, New York
    Harrisena, New York is a small hamlet within the town of Queensbury in Warren County, known for its rural character in the Adirondack region.
  • D. Valhalla, New York
    Valhalla, New York is a hamlet in the town of Mount Pleasant in Westchester County, known for its suburban character and several notable cemeteries and memorial sites.
  • E. Rensselaer
    Rensselaer is a masculine given name of English origin, now rare, that has historically appeared in the United States.
  • 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_69d827980cbc8190a0c569ae3940a1d9 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69ded6084574819098033a9723f3e1c4 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b6966e88190a0ed475b22a77cf1 completed May 8, 2026, 11:02 p.m.
NEDg Description generation batch_69fe6d199298819081207e27dfdf485f completed May 8, 2026, 11:09 p.m.
NED2 Entity disambiguation (via description) batch_69fe6de49480819087b36c070c434bf7 completed May 8, 2026, 11:12 p.m.
Created at: April 10, 2026, 2:11 a.m.