Triple

T566413
Position Surface form Disambiguated ID Type / Status
Subject Alexandre Dumas E13562 entity
Predicate placeOfBirth P1 FINISHED
Object Aisne
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
 E83838 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: Aisne | Statement: [Alexandre Dumas, placeOfBirth, Aisne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Aisne
Context triple: [Alexandre Dumas, placeOfBirth, Aisne]
  • A. Marne
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • B. Nièvre
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • C. Yonne
    Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
  • D. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • E. Oise
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near 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: Aisne
Triple: [Alexandre Dumas, placeOfBirth, Aisne]
Generated description
Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Aisne
Target entity description: Aisne is a department in northern France known for its historic towns, World War I battlefields, and rural landscapes.
  • A. Marne
    The Marne is a major river in northeastern France that flows through the Île-de-France region before joining the Seine near Paris.
  • B. Nièvre
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • C. Yonne
    Yonne is a major river in north-central France that flows through the Burgundy region before joining the Seine.
  • D. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • E. Oise
    Oise is a major river in northern France that flows through regions such as Picardy and Île-de-France before joining the Seine near 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b01aca48190944408d066519149 completed March 1, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc8ff78c8190954d33f9e4556cca completed March 2, 2026, 6:53 p.m.
NEDg Description generation batch_69a5de26ff1081908a60b55a1deab804 completed March 2, 2026, 6:59 p.m.
NED2 Entity disambiguation (via description) batch_69a5ff1ac6f481909915fd5b2e648558 completed March 2, 2026, 9:20 p.m.
Created at: March 1, 2026, 7:32 p.m.