Triple

T2642520
Position Surface form Disambiguated ID Type / Status
Subject Alfa Pendular E62902 entity
Predicate safetySystem P840 FINISHED
Object CONVEL
CONVEL is a train control and safety system used on Portugal’s high-speed Alfa Pendular services to monitor and protect train operations.
 E285811 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: CONVEL | Statement: [Alfa Pendular, safetySystem, CONVEL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CONVEL
Context triple: [Alfa Pendular, safetySystem, CONVEL]
  • A. Grocon
    Grocon is a major Australian construction and development company known for delivering large-scale commercial and residential projects.
  • B. Cavos
    Cavos is a surname most notably associated with Albert Cavos, a prominent 19th-century architect known for designing major theaters in Russia.
  • C. Passu Cones
    Passu Cones are a striking group of sharply pointed mountain peaks in Pakistan’s Hunza Valley, renowned for their dramatic, jagged skyline within the Karakoram range.
  • D. von Le Coq
    von Le Coq is the surname of Albert von Le Coq, a notable German archaeologist and explorer known for his expeditions in Central Asia.
  • E. ParCo
    ParCo is the official archaeological park authority that manages and promotes Rome’s Colosseum and its surrounding ancient sites.
  • 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: CONVEL
Triple: [Alfa Pendular, safetySystem, CONVEL]
Generated description
CONVEL is a train control and safety system used on Portugal’s high-speed Alfa Pendular services to monitor and protect train operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CONVEL
Target entity description: CONVEL is a train control and safety system used on Portugal’s high-speed Alfa Pendular services to monitor and protect train operations.
  • A. Grocon
    Grocon is a major Australian construction and development company known for delivering large-scale commercial and residential projects.
  • B. Cavos
    Cavos is a surname most notably associated with Albert Cavos, a prominent 19th-century architect known for designing major theaters in Russia.
  • C. Passu Cones
    Passu Cones are a striking group of sharply pointed mountain peaks in Pakistan’s Hunza Valley, renowned for their dramatic, jagged skyline within the Karakoram range.
  • D. von Le Coq
    von Le Coq is the surname of Albert von Le Coq, a notable German archaeologist and explorer known for his expeditions in Central Asia.
  • E. ParCo
    ParCo is the official archaeological park authority that manages and promotes Rome’s Colosseum and its surrounding ancient sites.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8ff34988190ba9d69ce9d77c71d completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98bfd4008190a30675ebaf01e483 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af99416924819099d4acb1a2d60e0c completed March 10, 2026, 4:08 a.m.
NED2 Entity disambiguation (via description) batch_69af99adadb08190a44f2286b25bf0aa completed March 10, 2026, 4:10 a.m.
Created at: March 6, 2026, 9:53 p.m.