Triple

T1139049
Position Surface form Disambiguated ID Type / Status
Subject Fier River E23406 entity
Predicate flowsThrough P225 FINISHED
Object Annecy agglomeration
Annecy agglomeration is an urban area in southeastern France centered on the city of Annecy, known for its lakeside setting, Alpine surroundings, and role as a regional economic and cultural hub.
 E214359 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: Annecy agglomeration | Statement: [Fier River, flowsThrough, Annecy agglomeration]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Annecy agglomeration
Context triple: [Fier River, flowsThrough, Annecy agglomeration]
  • A. Pays de Gex
    Pays de Gex is a region in eastern France near the Swiss border, known for its proximity to Geneva and the Jura Mountains.
  • B. Thoiry
    Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Chambéry
    Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
  • D. Laconnex
    Laconnex is a small rural municipality in western Switzerland, located in the canton of Geneva near the French border.
  • E. Grenoble
    Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
  • 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: Annecy agglomeration
Triple: [Fier River, flowsThrough, Annecy agglomeration]
Generated description
Annecy agglomeration is an urban area in southeastern France centered on the city of Annecy, known for its lakeside setting, Alpine surroundings, and role as a regional economic and cultural hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Annecy agglomeration
Target entity description: Annecy agglomeration is an urban area in southeastern France centered on the city of Annecy, known for its lakeside setting, Alpine surroundings, and role as a regional economic and cultural hub.
  • A. Pays de Gex
    Pays de Gex is a region in eastern France near the Swiss border, known for its proximity to Geneva and the Jura Mountains.
  • B. Thoiry
    Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
  • C. Chambéry
    Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
  • D. Laconnex
    Laconnex is a small rural municipality in western Switzerland, located in the canton of Geneva near the French border.
  • E. Grenoble
    Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc27c88881909c64ec30b7f66575 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3a85f8481908d93f60b0ae82901 completed March 8, 2026, 10:09 p.m.
NEDg Description generation batch_69adf431c3a88190971f61d53c2bad2e completed March 8, 2026, 10:12 p.m.
NED2 Entity disambiguation (via description) batch_69adf4bdb6dc8190964e5e78abfb8e40 completed March 8, 2026, 10:14 p.m.
Created at: March 1, 2026, 7:44 p.m.