Triple

T13528812
Position Surface form Disambiguated ID Type / Status
Subject Progress-M1 E323079 entity
Predicate rendezvousSystem P110704 FINISHED
Object Kurs
Kurs is a Russian automated docking and rendezvous system used to guide spacecraft in approaching and docking with orbital stations like Mir and the International Space Station.
E1044073 NE FINISHED

How this triple was built (5 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: Kurs | Statement: [Progress-M1, rendezvousSystem, Kurs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kurs
Context triple: [Progress-M1, rendezvousSystem, Kurs]
  • A. Corsi
    Corsi is the native name used by Corsicans to refer to themselves as a people.
  • B. Klassen
    Klassen is a surname most notably associated with Canadian speed skater and Olympic medalist Cindy Klassen.
  • C. Lesson
    Lesson is a French surname most notably borne by René Primevère Lesson, a 19th-century French surgeon, naturalist, and explorer.
  • D. Kurstin
    Kurstin is the surname of Greg Kurstin, a prominent American record producer, songwriter, and multi-instrumentalist known for his work with major pop and rock artists.
  • E. Lessons
    Lessons is a 2022 novel by Ian McEwan that follows a man's life across decades of personal and historical upheaval, exploring memory, trauma, and the passage of time.
  • 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: Kurs
Triple: [Progress-M1, rendezvousSystem, Kurs]
Generated description
Kurs is a Russian automated docking and rendezvous system used to guide spacecraft in approaching and docking with orbital stations like Mir and the International Space Station.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kurs
Target entity description: Kurs is a Russian automated docking and rendezvous system used to guide spacecraft in approaching and docking with orbital stations like Mir and the International Space Station.
  • A. Corsi
    Corsi is the native name used by Corsicans to refer to themselves as a people.
  • B. Klassen
    Klassen is a surname most notably associated with Canadian speed skater and Olympic medalist Cindy Klassen.
  • C. Lesson
    Lesson is a French surname most notably borne by René Primevère Lesson, a 19th-century French surgeon, naturalist, and explorer.
  • D. Kurstin
    Kurstin is the surname of Greg Kurstin, a prominent American record producer, songwriter, and multi-instrumentalist known for his work with major pop and rock artists.
  • E. Lessons
    Lessons is a 2022 novel by Ian McEwan that follows a man's life across decades of personal and historical upheaval, exploring memory, trauma, and the passage of time.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rendezvousSystem
Context triple: [Progress-M1, rendezvousSystem, Kurs]
  • A. rendezvousTarget
    Indicates that one entity is designated as the meeting or rendezvous point for another entity.
  • B. rendezvousType
    Indicates the specific kind or category of meeting or rendezvous that occurs between entities.
  • C. rendezvousCapability
    Indicates the ability of one entity to meet or dock with another entity at a planned place and time.
  • D. rendezvousWith
    Indicates that two or more entities meet or come together at an agreed place and time, often for a specific purpose.
  • E. rendezvousProfile
    Indicates a relationship where entities coordinate to meet at a specific place and time, often under predefined conditions or plans.
  • F. None of above. chosen

Provenance (7 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafba2c308190873efd15dfe26358 completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549dda6481908e9305690488b1af completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f755521abc8190baabcec69e80d554 completed May 3, 2026, 2:01 p.m.
NED2 Entity disambiguation (via description) batch_69f755c52c648190a4912725ce65ff04 completed May 3, 2026, 2:03 p.m.
PD Predicate disambiguation batch_69dbae1046c48190b4ee98c6c9cb9d85 completed April 12, 2026, 2:37 p.m.
PDg Predicate description generation batch_69dbaecc98cc8190829f5be759c4f1e3 completed April 12, 2026, 2:40 p.m.
Created at: April 9, 2026, 9:44 p.m.