Triple

T3875647
Position Surface form Disambiguated ID Type / Status
Subject Venus Express E92493 entity
Predicate instrument P792 FINISHED
Object VeRa
VeRa is a radio science experiment on the Venus Express spacecraft designed to study Venus’s atmosphere, ionosphere, and gravity field using radio occultation and tracking techniques.
 E394674 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: VeRa | Statement: [Venus Express, instrument, VeRa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VeRa
Context triple: [Venus Express, instrument, VeRa]
  • A. Reva
    Reva is an alternative name for the Narmada River, one of central India’s major and holiest rivers.
  • B. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • C. Vera
    Vera is a feminine given name of Slavic origin, commonly used in Russian and other Eastern European cultures, meaning "faith."
  • D. Vera
    Vera is a memorable supporting character from the 1989 Eddie Murphy film "Harlem Nights," known for her tough, comedic persona.
  • E. Vara
    Vara is a short form of the female given name Varvara, commonly used in Slavic languages.
  • 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: VeRa
Triple: [Venus Express, instrument, VeRa]
Generated description
VeRa is a radio science experiment on the Venus Express spacecraft designed to study Venus’s atmosphere, ionosphere, and gravity field using radio occultation and tracking techniques.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VeRa
Target entity description: VeRa is a radio science experiment on the Venus Express spacecraft designed to study Venus’s atmosphere, ionosphere, and gravity field using radio occultation and tracking techniques.
  • A. Reva
    Reva is an alternative name for the Narmada River, one of central India’s major and holiest rivers.
  • B. Vera
    Vera is a memorable supporting character from the 1989 Eddie Murphy film "Harlem Nights," known for her tough, comedic persona.
  • C. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • D. Vera
    Vera is a feminine given name of Slavic origin, commonly used in Russian and other Eastern European cultures, meaning "faith."
  • E. Vara
    Vara is a short form of the female given name Varvara, commonly used in Slavic languages.
  • 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_69aed967448c819086c4b358d37b25aa completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeec706434819095e0d2b376adb548 completed March 9, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5124f095881909143b624128ff569 completed March 14, 2026, 7:46 a.m.
NEDg Description generation batch_69b512f4041081908eb32ae059681afa completed March 14, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69b5137200a08190bd2a78398e03803e completed March 14, 2026, 7:51 a.m.
Created at: March 9, 2026, 3:20 p.m.