Triple

T12174488
Position Surface form Disambiguated ID Type / Status
Subject Arianespace E290053 entity
Predicate notableCustomer P7186 FINISHED
Object SES S.A.
SES S.A. is a leading global satellite operator based in Luxembourg that provides satellite communications services for broadcasters, governments, and network operators worldwide.
 E962780 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: SES S.A. | Statement: [Arianespace, notableCustomer, SES S.A.]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SES S.A.
Context triple: [Arianespace, notableCustomer, SES S.A.]
  • A. Total S.A.
    Total S.A. was the former name of TotalEnergies, a major French multinational energy company involved in oil, gas, and increasingly renewable energy.
  • B. GDF Suez
    GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
  • C. Vinci SA
    Vinci SA is a major French multinational concessions and construction company specializing in infrastructure development and management worldwide.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Thales Group
    Thales Group is a French multinational company specializing in aerospace, defense, security, and transportation technologies and systems.
  • 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: SES S.A.
Triple: [Arianespace, notableCustomer, SES S.A.]
Generated description
SES S.A. is a leading global satellite operator based in Luxembourg that provides satellite communications services for broadcasters, governments, and network operators worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SES S.A.
Target entity description: SES S.A. is a leading global satellite operator based in Luxembourg that provides satellite communications services for broadcasters, governments, and network operators worldwide.
  • A. Total S.A.
    Total S.A. was the former name of TotalEnergies, a major French multinational energy company involved in oil, gas, and increasingly renewable energy.
  • B. GDF Suez
    GDF Suez was a major French multinational energy company, primarily active in electricity and natural gas, that later rebranded as Engie.
  • C. Vinci SA
    Vinci SA is a major French multinational concessions and construction company specializing in infrastructure development and management worldwide.
  • D. Tractebel
    Tractebel is an international engineering and consulting company specializing in energy, water, and infrastructure projects.
  • E. Thales Group
    Thales Group is a French multinational company specializing in aerospace, defense, security, and transportation technologies and systems.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915dc71788190bdaadf7be9d8d6ce completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6a9482481909500c216f23fceb4 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f5fdebe3fc81909a5bb23a943c3c43 completed May 2, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_69f5feeeeb2081908191b1c2d1c2fbfd completed May 2, 2026, 1:41 p.m.
Created at: April 8, 2026, 9:50 p.m.