Triple

T13813008
Position Surface form Disambiguated ID Type / Status
Subject Olympic House, Lausanne E331941 entity
Predicate structuralEngineer P616 FINISHED
Object Ingérop
Ingérop is a French engineering consultancy firm known for its work in structural, civil, and infrastructure projects worldwide.
 E1063120 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: Ingérop | Statement: [Olympic House, Lausanne, structuralEngineer, Ingérop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ingérop
Context triple: [Olympic House, Lausanne, structuralEngineer, Ingérop]
  • A. Rositsa
    Rositsa is a river in northern Bulgaria that serves as a significant tributary of the Yantra River.
  • B. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • C. Vassy
    Vassy is a commune in northeastern France historically known as the site of the 1562 Massacre of Vassy, an event that helped ignite the French Wars of Religion.
  • D. Vladimira
    Vladimira is a feminine given name, primarily used in Slavic cultures, derived from the male name Vladimir.
  • E. Serafima
    Serafima is a feminine given name of Slavic origin, commonly used in Russian-speaking countries.
  • 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: Ingérop
Triple: [Olympic House, Lausanne, structuralEngineer, Ingérop]
Generated description
Ingérop is a French engineering consultancy firm known for its work in structural, civil, and infrastructure projects worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ingérop
Target entity description: Ingérop is a French engineering consultancy firm known for its work in structural, civil, and infrastructure projects worldwide.
  • A. Rositsa
    Rositsa is a river in northern Bulgaria that serves as a significant tributary of the Yantra River.
  • B. Aloysya
    Aloysya is a given name, typically a feminine variant of Aloysius, used in various cultures and languages.
  • C. Vassy
    Vassy is a commune in northeastern France historically known as the site of the 1562 Massacre of Vassy, an event that helped ignite the French Wars of Religion.
  • D. Vladimira
    Vladimira is a feminine given name, primarily used in Slavic cultures, derived from the male name Vladimir.
  • E. Serafima
    Serafima is a feminine given name of Slavic origin, commonly used in Russian-speaking countries.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de027198f8819095da3e714ac241f5 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8de34a4819090c99cb78b941003 completed May 3, 2026, 9:06 p.m.
NEDg Description generation batch_69f7b974fce88190ace5030555b7b5f1 completed May 3, 2026, 9:09 p.m.
NED2 Entity disambiguation (via description) batch_69f7ba936c4481908757699ff22d3904 completed May 3, 2026, 9:13 p.m.
Created at: April 9, 2026, 10:12 p.m.