Triple

T10953512
Position Surface form Disambiguated ID Type / Status
Subject canton of Brienne-le-Château E258782 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Blignicourt
Blignicourt is a small commune in the Aube department of north-central France.
 E908274 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: Blignicourt | Statement: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Blignicourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blignicourt
Context triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Blignicourt]
  • A. Morlaincourt
    Morlaincourt is a small commune in northeastern France, likely known locally for its rural character and proximity to the Yonne river’s headwaters.
  • B. Bétignicourt
    Bétignicourt is a small commune in the Aube department in north-central France.
  • C. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • D. Dolancourt
    Dolancourt is a small commune in northeastern France’s Grand Est region, known for hosting the Nigloland amusement park.
  • E. 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.
  • 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: Blignicourt
Triple: [canton of Brienne-le-Château, containsAdministrativeTerritorialEntity, Blignicourt]
Generated description
Blignicourt is a small commune in the Aube department of north-central France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blignicourt
Target entity description: Blignicourt is a small commune in the Aube department of north-central France.
  • A. Morlaincourt
    Morlaincourt is a small commune in northeastern France, likely known locally for its rural character and proximity to the Yonne river’s headwaters.
  • B. Bétignicourt
    Bétignicourt is a small commune in the Aube department in north-central France.
  • C. Juvancourt
    Juvancourt is a small commune in the Aube department in north-central France.
  • D. Dolancourt
    Dolancourt is a small commune in northeastern France’s Grand Est region, known for hosting the Nigloland amusement park.
  • E. 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.
  • 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_69e46283f41c8190ac3e1f196c5e4ca0 completed April 19, 2026, 5:05 a.m.
NEDg Description generation batch_69e46c3448348190b2c062d21771066d completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e46dadbc5c8190b41279a05731dc95 completed April 19, 2026, 5:52 a.m.
Created at: April 8, 2026, 9:23 p.m.