Triple

T15403925
Position Surface form Disambiguated ID Type / Status
Subject Aisne E368397 entity
Predicate hasLeftTributary P415 FINISHED
Object Ailette
The Ailette is a small river in northern France that flows through the Aisne department and feeds into the Aisne River.
 E1155318 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: Ailette | Statement: [Aisne, hasLeftTributary, Ailette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ailette
Context triple: [Aisne, hasLeftTributary, Ailette]
  • A. Aileu
    Aileu is a mountainous inland municipality in central East Timor known for its rural communities and use of the Mambae language.
  • B. Elke
    Elke is a feminine given name of German origin commonly used in German-speaking countries.
  • C. Malaita
    Malaita is one of the main islands of the Solomon Islands in the South Pacific, known for its large population, rich traditional culture, and historical role in regional labor trade.
  • D. Aulla
    Aulla is a small historic town in northern Tuscany, Italy, known for its medieval fortifications and strategic location in the Lunigiana region.
  • E. Ainley
    Ainley is an English surname most notably associated with actor Anthony Ainley, known for his role as the Master in the classic Doctor Who series.
  • 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: Ailette
Triple: [Aisne, hasLeftTributary, Ailette]
Generated description
The Ailette is a small river in northern France that flows through the Aisne department and feeds into the Aisne River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ailette
Target entity description: The Ailette is a small river in northern France that flows through the Aisne department and feeds into the Aisne River.
  • A. Aileu
    Aileu is a mountainous inland municipality in central East Timor known for its rural communities and use of the Mambae language.
  • B. Elke
    Elke is a feminine given name of German origin commonly used in German-speaking countries.
  • C. Malaita
    Malaita is one of the main islands of the Solomon Islands in the South Pacific, known for its large population, rich traditional culture, and historical role in regional labor trade.
  • D. Aulla
    Aulla is a small historic town in northern Tuscany, Italy, known for its medieval fortifications and strategic location in the Lunigiana region.
  • E. Ainley
    Ainley is an English surname most notably associated with actor Anthony Ainley, known for his role as the Master in the classic Doctor Who series.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8fde64819082ec0c68df305561 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff13584f8881908b2527c51f85ae28 completed May 9, 2026, 10:58 a.m.
NEDg Description generation batch_69ff145ac8e081908b075cee67e82aa3 completed May 9, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69ff1509e5a48190b69f1a44d793e07d completed May 9, 2026, 11:05 a.m.
Created at: April 10, 2026, 3:19 a.m.