Triple

T401366
Position Surface form Disambiguated ID Type / Status
Subject Lake Neuchâtel E9289 entity
Predicate inflow P415 FINISHED
Object Areuse
Areuse is a river in western Switzerland that flows through the Jura Mountains and picturesque gorges before emptying into Lake Neuchâtel.
 E50851 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: Areuse | Statement: [Lake Neuchâtel, inflow, Areuse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Areuse
Context triple: [Lake Neuchâtel, inflow, Areuse]
  • A. Usk
    Usk is a small historic town in Monmouthshire, southeast Wales, known for its medieval castle and picturesque setting on the River Usk.
  • B. Avusy
    Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
  • C. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • D. Nitria
    Nitria was one of the earliest and most important Christian monastic centers in the Egyptian desert, renowned as a hub of the Desert Fathers’ ascetic life.
  • E. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • 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: Areuse
Triple: [Lake Neuchâtel, inflow, Areuse]
Generated description
Areuse is a river in western Switzerland that flows through the Jura Mountains and picturesque gorges before emptying into Lake Neuchâtel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Areuse
Target entity description: Areuse is a river in western Switzerland that flows through the Jura Mountains and picturesque gorges before emptying into Lake Neuchâtel.
  • A. Usk
    Usk is a small historic town in Monmouthshire, southeast Wales, known for its medieval castle and picturesque setting on the River Usk.
  • B. Avusy
    Avusy is a small rural municipality located in the canton of Geneva in southwestern Switzerland, near the French border.
  • C. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • D. Nitria
    Nitria was one of the earliest and most important Christian monastic centers in the Egyptian desert, renowned as a hub of the Desert Fathers’ ascetic life.
  • E. Beni
    Beni is a sparsely populated, largely Amazonian department in northeastern Bolivia known for its tropical lowlands, cattle ranching, and rich indigenous cultures.
  • 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_69a2e8004cb88190b92ed1add6abf41a completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ec9f77888190bcc2bc68d201ed35 completed Feb. 28, 2026, 1:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69a410410c108190990d4d5ef2e7ff61 completed March 1, 2026, 10:09 a.m.
NEDg Description generation batch_69a410ce17ac8190a3ac2325e36cf6b3 completed March 1, 2026, 10:11 a.m.
NED2 Entity disambiguation (via description) batch_69a41125951c8190accbf273ef677206 completed March 1, 2026, 10:12 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.