Triple

T14690114
Position Surface form Disambiguated ID Type / Status
Subject Great Stallion E345013 entity
Predicate languageName P13426 FINISHED
Object Vezhof
Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
E1114262 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: Vezhof | Statement: [Great Stallion, languageName, Vezhof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vezhof
Context triple: [Great Stallion, languageName, Vezhof]
  • A. Vollenhoven
    Vollenhoven is a Dutch surname most notably associated with philosopher D. H. Th. Vollenhoven, a key figure in Reformational philosophy.
  • B. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • C. Reeshof
    Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
  • D. Veenendaal
    Veenendaal is a Dutch town and municipality in the central Netherlands, known for its location between Utrecht and the Veluwe and its mix of residential, commercial, and light industrial areas.
  • E. Valkenburg
    Valkenburg is a village in the Dutch province of South Holland, known for its historic charm and proximity to the North Sea coast.
  • 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: Vezhof
Triple: [Great Stallion, languageName, Vezhof]
Generated description
Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vezhof
Target entity description: Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
  • A. Vollenhoven
    Vollenhoven is a Dutch surname most notably associated with philosopher D. H. Th. Vollenhoven, a key figure in Reformational philosophy.
  • B. Woudenberg
    Woudenberg is a small Dutch municipality and town located in the central Netherlands.
  • C. Reeshof
    Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
  • D. Veenendaal
    Veenendaal is a Dutch town and municipality in the central Netherlands, known for its location between Utrecht and the Veluwe and its mix of residential, commercial, and light industrial areas.
  • E. Valkenburg
    Valkenburg is a village in the Dutch province of South Holland, known for its historic charm and proximity to the North Sea coast.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb5844de481908a796eaa474bfde9 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde189771c81909289b8b044e32547 completed May 8, 2026, 1:13 p.m.
NEDg Description generation batch_69fde5fd6854819083957f2c653eb8b6 completed May 8, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69fde6ffc27881909427d24560011cdf completed May 8, 2026, 1:37 p.m.
Created at: April 10, 2026, 1:28 a.m.