Triple

T16469914
Position Surface form Disambiguated ID Type / Status
Subject Canton of Moreuil E400032 entity
Predicate containsCommune P15149 FINISHED
Object Beaucourt-en-Santerre
Beaucourt-en-Santerre is a small rural commune in the Somme department of northern France, situated within the historical region of Picardy.
 E1215450 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: Beaucourt-en-Santerre | Statement: [Canton of Moreuil, containsCommune, Beaucourt-en-Santerre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Beaucourt-en-Santerre
Context triple: [Canton of Moreuil, containsCommune, Beaucourt-en-Santerre]
  • A. Beaucourt
    Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
  • B. Bessancourt
    Bessancourt is a small suburban commune in the Val-d'Oise department in the Île-de-France region of northern France, forming part of the northwestern outskirts of Paris.
  • C. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • D. Rosières-en-Santerre
    Rosières-en-Santerre is a commune in the Somme department of northern France, situated in the historical region of Picardy.
  • E. Bétignicourt
    Bétignicourt is a small commune in the Aube department in north-central France.
  • 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: Beaucourt-en-Santerre
Triple: [Canton of Moreuil, containsCommune, Beaucourt-en-Santerre]
Generated description
Beaucourt-en-Santerre is a small rural commune in the Somme department of northern France, situated within the historical region of Picardy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Beaucourt-en-Santerre
Target entity description: Beaucourt-en-Santerre is a small rural commune in the Somme department of northern France, situated within the historical region of Picardy.
  • A. Beaucourt
    Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
  • B. Bessancourt
    Bessancourt is a small suburban commune in the Val-d'Oise department in the Île-de-France region of northern France, forming part of the northwestern outskirts of Paris.
  • C. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • D. Rosières-en-Santerre
    Rosières-en-Santerre is a commune in the Somme department of northern France, situated in the historical region of Picardy.
  • E. Bétignicourt
    Bétignicourt is a small commune in the Aube department in north-central France.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32dcfed6c8190b8dbe4b65b0ab817 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f5af4308190bd023624de35027f completed May 10, 2026, 9:26 a.m.
NEDg Description generation batch_6a0050c5d4548190a674c1c19f08a9fd completed May 10, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a0051a7ae208190b33d42cc8d4bb21f completed May 10, 2026, 9:36 a.m.
Created at: April 10, 2026, 5:11 a.m.