Triple

T10209239
Position Surface form Disambiguated ID Type / Status
Subject Siemens Mobility E242282 entity
Predicate brand P1500 FINISHED
Object Velaro
Velaro is a family of high-speed electric multiple unit trains developed by Siemens for use on major rail networks worldwide.
E849517 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: Velaro | Statement: [Siemens Mobility, brand, Velaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velaro
Context triple: [Siemens Mobility, brand, Velaro]
  • A. Biqueli
    Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
  • B. Morini
    The Morini were an ancient Belgic tribe inhabiting the coastal region of what is now northern France and southwestern Belgium during the Iron Age and Roman period.
  • C. Auta
    Auta is a small settlement on the island of Mitiaro in the Cook Islands.
  • D. Rimac
    Rimac is a Croatian automotive company renowned for developing high-performance electric hypercars and advanced EV technologies used by major luxury and sports car manufacturers.
  • E. LJ Torana
    LJ Torana is a model of the Holden Torana, a compact Australian car produced by Holden in the early 1970s and popular in both everyday use and motorsport.
  • 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: Velaro
Triple: [Siemens Mobility, brand, Velaro]
Generated description
Velaro is a family of high-speed electric multiple unit trains developed by Siemens for use on major rail networks worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Velaro
Target entity description: Velaro is a family of high-speed electric multiple unit trains developed by Siemens for use on major rail networks worldwide.
  • A. Biqueli
    Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
  • B. Morini
    The Morini were an ancient Belgic tribe inhabiting the coastal region of what is now northern France and southwestern Belgium during the Iron Age and Roman period.
  • C. Auta
    Auta is a small settlement on the island of Mitiaro in the Cook Islands.
  • D. Rimac
    Rimac is a Croatian automotive company renowned for developing high-performance electric hypercars and advanced EV technologies used by major luxury and sports car manufacturers.
  • E. LJ Torana
    LJ Torana is a model of the Holden Torana, a compact Australian car produced by Holden in the early 1970s and popular in both everyday use and motorsport.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d395fa86cc8190b4f115b5a0f99772 completed April 6, 2026, 11:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d652cca9c081909f705365c70db009 completed April 8, 2026, 1:06 p.m.
NEDg Description generation batch_69d654ddaed88190bcd7f1a2ee9dd462 completed April 8, 2026, 1:15 p.m.
NED2 Entity disambiguation (via description) batch_69d655338cc08190ba00163f0afa4c3b completed April 8, 2026, 1:16 p.m.
Created at: April 6, 2026, 10:59 a.m.