Triple

T14723496
Position Surface form Disambiguated ID Type / Status
Subject Orne E345874 entity
Predicate contains P35 FINISHED
Object L’Aigle
L’Aigle is a small historic town in northwestern France known for its role in the Orne department and its traditional Norman character.
 E1115334 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: L’Aigle | Statement: [Orne, contains, L’Aigle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L’Aigle
Context triple: [Orne, contains, L’Aigle]
  • A. Aigle
    Aigle is a historic town in southwestern Switzerland known for its medieval castle and surrounding vineyards in the canton of Vaud.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Hamois
    Hamois is a rural municipality in the Walloon region of Belgium, known for its agricultural landscapes and traditional villages within the Condroz area.
  • D. Mont Colombier
    Mont Colombier is a prominent peak in the French Alps known for its panoramic views over the Bauges massif and surrounding alpine landscapes.
  • E. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • 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: L’Aigle
Triple: [Orne, contains, L’Aigle]
Generated description
L’Aigle is a small historic town in northwestern France known for its role in the Orne department and its traditional Norman character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L’Aigle
Target entity description: L’Aigle is a small historic town in northwestern France known for its role in the Orne department and its traditional Norman character.
  • A. Aigle
    Aigle is a historic town in southwestern Switzerland known for its medieval castle and surrounding vineyards in the canton of Vaud.
  • B. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • C. Hamois
    Hamois is a rural municipality in the Walloon region of Belgium, known for its agricultural landscapes and traditional villages within the Condroz area.
  • D. Mont Colombier
    Mont Colombier is a prominent peak in the French Alps known for its panoramic views over the Bauges massif and surrounding alpine landscapes.
  • E. Sauvestre
    Sauvestre is a French surname most notably associated with architect Stephen Sauvestre, who contributed to the design of the Eiffel Tower.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec25e9a14819081fa06fc601f295d completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf09791e081908a1262717fd31445 completed May 8, 2026, 2:17 p.m.
NEDg Description generation batch_69fdf32c1ec48190b28fb67e00b87fcd completed May 8, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_69fdf3cfd7b48190b5d6177c5bf0e42e completed May 8, 2026, 2:31 p.m.
Created at: April 10, 2026, 1:29 a.m.