Triple

T10953525
Position Surface form Disambiguated ID Type / Status
Subject canton of Brienne-le-Château E258782 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Lassicourt
Lassicourt is a small commune in the Aube department of north-central France, situated within the Grand Est region.
E915805 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: Lassicourt | Statement: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Lassicourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lassicourt
Context triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Lassicourt]
  • A. Livarot
    Livarot is a small town in the Normandy region of northwestern France, historically known for its production of the pungent Livarot cheese.
  • B. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Roquebillière
    Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
  • E. Groslay
    Groslay is a small suburban commune in the Val-d'Oise department in northern France, forming part of 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: Lassicourt
Triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Lassicourt]
Generated description
Lassicourt is a small commune in the Aube department of north-central France, situated within the Grand Est region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lassicourt
Target entity description: Lassicourt is a small commune in the Aube department of north-central France, situated within the Grand Est region.
  • A. Livarot
    Livarot is a small town in the Normandy region of northwestern France, historically known for its production of the pungent Livarot cheese.
  • B. Vauvert
    Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
  • C. Gressy
    Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
  • D. Roquebillière
    Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
  • E. Groslay
    Groslay is a small suburban commune in the Val-d'Oise department in northern France, forming part of 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_69d6aa88500c819097d7032ca578e74f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770fe4cfc81909032296c31e077f0 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4f34d1e108190ad281dae6c92634e completed April 19, 2026, 3:22 p.m.
NEDg Description generation batch_69e4f9596e1081908e7b319f77453438 completed April 19, 2026, 3:48 p.m.
NED2 Entity disambiguation (via description) batch_69e4ff4645948190a2bfcc3a4efd8e2a completed April 19, 2026, 4:13 p.m.
Created at: April 8, 2026, 9:23 p.m.