Triple

T12975847
Position Surface form Disambiguated ID Type / Status
Subject Vinci SA E321520 entity
Predicate hasSubsidiary P254 FINISHED
Object Actemium
Actemium is an industrial engineering and services network specializing in improving and optimizing industrial processes across various sectors.
 E1012385 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: Actemium | Statement: [Vinci SA, hasSubsidiary, Actemium]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Actemium
Context triple: [Vinci SA, hasSubsidiary, Actemium]
  • A. Samnium
    Samnium was an ancient region of south-central Italy inhabited by the Samnites, an Oscan-speaking Italic people known for their wars with the Roman Republic.
  • B. Regulbium
    Regulbium was the Roman-era coastal fort and settlement that later became known as Reculver in Kent, England.
  • C. Novaesium
    Novaesium is the ancient Roman name for the settlement that developed into the modern German city of Neuss, an important military and trading post along the Rhine.
  • D. Agyrium
    Agyrium was an ancient city in central Sicily, historically significant as the birthplace of the Greek historian Diodorus Siculus.
  • E. Ormenium
    Ormenium was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources such as Homer’s Iliad.
  • 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: Actemium
Triple: [Vinci SA, hasSubsidiary, Actemium]
Generated description
Actemium is an industrial engineering and services network specializing in improving and optimizing industrial processes across various sectors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Actemium
Target entity description: Actemium is an industrial engineering and services network specializing in improving and optimizing industrial processes across various sectors.
  • A. Samnium
    Samnium was an ancient region of south-central Italy inhabited by the Samnites, an Oscan-speaking Italic people known for their wars with the Roman Republic.
  • B. Regulbium
    Regulbium was the Roman-era coastal fort and settlement that later became known as Reculver in Kent, England.
  • C. Novaesium
    Novaesium is the ancient Roman name for the settlement that developed into the modern German city of Neuss, an important military and trading post along the Rhine.
  • D. Agyrium
    Agyrium was an ancient city in central Sicily, historically significant as the birthplace of the Greek historian Diodorus Siculus.
  • E. Ormenium
    Ormenium was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources such as Homer’s Iliad.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e48c0208190bb7ec80780480b37 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8ec821c81909398d8e02d69dcbf completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9dc31ec819093c89ff0a1ccbfa1 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6baacd7548190af5514923a0dee26 completed May 3, 2026, 3:02 a.m.
Created at: April 9, 2026, 8:37 p.m.