Triple

T12463136
Position Surface form Disambiguated ID Type / Status
Subject Verzy E297849 entity
Predicate knownFor P22 FINISHED
Object Faux de Verzy
Faux de Verzy are a famous group of rare, naturally twisted dwarf beech trees located in the forest near Verzy in northeastern France.
 E984661 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: Faux de Verzy | Statement: [Verzy, knownFor, Faux de Verzy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Faux de Verzy
Context triple: [Verzy, knownFor, Faux de Verzy]
  • A. Boucicaut
    Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
  • B. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • C. Les Breuleux
    Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
  • D. La Gleize
    La Gleize is a village in the Belgian Ardennes best known as a major battlefield of the Battle of the Bulge during World War II.
  • E. La Verrière
    La Verrière is a suburban commune in the Yvelines department of north-central France, located within the Paris metropolitan area.
  • 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: Faux de Verzy
Triple: [Verzy, knownFor, Faux de Verzy]
Generated description
Faux de Verzy are a famous group of rare, naturally twisted dwarf beech trees located in the forest near Verzy in northeastern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Faux de Verzy
Target entity description: Faux de Verzy are a famous group of rare, naturally twisted dwarf beech trees located in the forest near Verzy in northeastern France.
  • A. Boucicaut
    Boucicaut is a station on the Paris Métro serving the 15th arrondissement of Paris.
  • B. Grand Veymont
    Grand Veymont is a prominent mountain peak in the French Prealps, known for its panoramic views and popular hiking routes within the Vercors region.
  • C. Les Breuleux
    Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
  • D. La Gleize
    La Gleize is a village in the Belgian Ardennes best known as a major battlefield of the Battle of the Bulge during World War II.
  • E. La Verrière
    La Verrière is a suburban commune in the Yvelines department of north-central France, located within the Paris metropolitan area.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94db5efe88190a76949e4ddc3314c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f1f44f481909c7efdffd2aeac41 completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f641a309cc8190b2403e62a6acfe58 completed May 2, 2026, 6:25 p.m.
NED2 Entity disambiguation (via description) batch_69f6427c162c8190ae2c027913d43b9e completed May 2, 2026, 6:29 p.m.
Created at: April 8, 2026, 9:56 p.m.