Triple

T9291173
Position Surface form Disambiguated ID Type / Status
Subject Somme (department) E223520 entity
Predicate containsTown P847 FINISHED
Object Flixecourt
Flixecourt is a small commune in northern France known historically for its textile industry and proximity to the Somme River.
 E790694 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: Flixecourt | Statement: [Somme (department), containsTown, Flixecourt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Flixecourt
Context triple: [Somme (department), containsTown, Flixecourt]
  • 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. Florennes
    Florennes is a municipality in the Wallonia region of Belgium, known for hosting a major military air base and its surrounding rural landscape.
  • C. Beaucourt
    Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
  • D. Dreux
    Dreux is a historic town in northern France known for its royal chapel and role as a regional center in the Eure-et-Loir department.
  • E. Flémalle
    Flémalle is a municipality in eastern Belgium known for its industrial heritage and location along the Meuse River in the province of Liège.
  • 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: Flixecourt
Triple: [Somme (department), containsTown, Flixecourt]
Generated description
Flixecourt is a small commune in northern France known historically for its textile industry and proximity to the Somme River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Flixecourt
Target entity description: Flixecourt is a small commune in northern France known historically for its textile industry and proximity to the Somme River.
  • 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. Florennes
    Florennes is a municipality in the Wallonia region of Belgium, known for hosting a major military air base and its surrounding rural landscape.
  • C. Beaucourt
    Beaucourt is a small French commune located in the northeastern region of Bourgogne-Franche-Comté near the Swiss border.
  • D. Dreux
    Dreux is a historic town in northern France known for its royal chapel and role as a regional center in the Eure-et-Loir department.
  • E. Flémalle
    Flémalle is a municipality in eastern Belgium known for its industrial heritage and location along the Meuse River in the province of Liège.
  • 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_69ca8422ddf881908a3f8f876c9f53aa completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd0865a7108190b807afd259980db2 completed April 1, 2026, 11:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b2381e2c8190acbecf97dea1200c completed April 4, 2026, 6:39 a.m.
NEDg Description generation batch_69d0b3a2b6f481908b0528f6fa67535b completed April 4, 2026, 6:45 a.m.
NED2 Entity disambiguation (via description) batch_69d0b7944adc819080b3a90878dd7203 completed April 4, 2026, 7:02 a.m.
Created at: March 30, 2026, 7:35 p.m.