Triple

T16469923
Position Surface form Disambiguated ID Type / Status
Subject Canton of Moreuil E400032 entity
Predicate containsCommune P15149 FINISHED
Object Hargicourt
Hargicourt is a small French commune located in the Somme department in northern France.
E1216546 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: Hargicourt | Statement: [Canton of Moreuil, containsCommune, Hargicourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hargicourt
Context triple: [Canton of Moreuil, containsCommune, Hargicourt]
  • A. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • B. Maurecourt
    Maurecourt is a small suburban commune in the Yvelines department of north-central France, located in the western outskirts of the Paris metropolitan area.
  • C. Fouquescourt
    Fouquescourt is a small rural commune in northern France’s Somme department, characterized by its agricultural landscape and traditional Picard village setting.
  • D. Berlencourt
    Berlencourt is a small commune in northern France, located within the Nord department in the Hauts-de-France region.
  • E. Breteuil
    Breteuil is a commune in northern France that serves as a local administrative and service hub for its surrounding rural 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: Hargicourt
Triple: [Canton of Moreuil, containsCommune, Hargicourt]
Generated description
Hargicourt is a small French commune located in the Somme department in northern France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hargicourt
Target entity description: Hargicourt is a small French commune located in the Somme department in northern France.
  • A. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • B. Maurecourt
    Maurecourt is a small suburban commune in the Yvelines department of north-central France, located in the western outskirts of the Paris metropolitan area.
  • C. Fouquescourt chosen
    Fouquescourt is a small rural commune in northern France’s Somme department, characterized by its agricultural landscape and traditional Picard village setting.
  • D. Berlencourt
    Berlencourt is a small commune in northern France, located within the Nord department in the Hauts-de-France region.
  • E. Breteuil
    Breteuil is a commune in northern France that serves as a local administrative and service hub for its surrounding rural area.
  • F. None of above.

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_6a006078da4c8190ba510d92b503e993 completed May 10, 2026, 10:39 a.m.
NEDg Description generation batch_6a0061a6e1e88190a5efe0430db0bd9b completed May 10, 2026, 10:44 a.m.
NED2 Entity disambiguation (via description) batch_6a00627908988190803707069872e4c5 completed May 10, 2026, 10:48 a.m.
Created at: April 10, 2026, 5:11 a.m.