Triple

T8739556
Position Surface form Disambiguated ID Type / Status
Subject Gemini 9A E207466 entity
Predicate rendezvousTarget P84583 FINISHED
Object Augmented Target Docking Adapter
The Augmented Target Docking Adapter was a modified Agena target vehicle used in NASA’s Gemini program to test and practice orbital rendezvous and docking techniques.
E755783 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: Augmented Target Docking Adapter | Statement: [Gemini 9A, rendezvousTarget, Augmented Target Docking Adapter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Augmented Target Docking Adapter
Context triple: [Gemini 9A, rendezvousTarget, Augmented Target Docking Adapter]
  • A. Kvant docking module
    The Kvant docking module was an add-on component of the Mir space station that provided additional docking ports and support for visiting spacecraft and modules.
  • B. Kurs automatic docking system
    The Kurs automatic docking system is a Russian radio-based guidance and control technology used to autonomously dock spacecraft, such as Progress and Soyuz, with space stations like Mir and the International Space Station.
  • C. Omni-Purpose Apparatus for LEP
    Omni-Purpose Apparatus for LEP (OPAL) was a major particle physics detector experiment at CERN’s Large Electron–Positron Collider that played a key role in precision tests of the Standard Model.
  • D. Adept AI
    Adept AI is an artificial intelligence research and product company focused on building AI agents that can use existing software tools to perform complex tasks for users.
  • E. NASA Docking System (Crew Dragon)
    The NASA Docking System (Crew Dragon) is the standardized, automated interface that enables SpaceX’s Crew Dragon spacecraft to safely and reliably dock with the International Space Station and other compatible orbital platforms.
  • 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: Augmented Target Docking Adapter
Triple: [Gemini 9A, rendezvousTarget, Augmented Target Docking Adapter]
Generated description
The Augmented Target Docking Adapter was a modified Agena target vehicle used in NASA’s Gemini program to test and practice orbital rendezvous and docking techniques.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Augmented Target Docking Adapter
Target entity description: The Augmented Target Docking Adapter was a modified Agena target vehicle used in NASA’s Gemini program to test and practice orbital rendezvous and docking techniques.
  • A. Kvant docking module
    The Kvant docking module was an add-on component of the Mir space station that provided additional docking ports and support for visiting spacecraft and modules.
  • B. Kurs automatic docking system
    The Kurs automatic docking system is a Russian radio-based guidance and control technology used to autonomously dock spacecraft, such as Progress and Soyuz, with space stations like Mir and the International Space Station.
  • C. Omni-Purpose Apparatus for LEP
    Omni-Purpose Apparatus for LEP (OPAL) was a major particle physics detector experiment at CERN’s Large Electron–Positron Collider that played a key role in precision tests of the Standard Model.
  • D. Adept AI
    Adept AI is an artificial intelligence research and product company focused on building AI agents that can use existing software tools to perform complex tasks for users.
  • E. NASA Docking System (Crew Dragon)
    The NASA Docking System (Crew Dragon) is the standardized, automated interface that enables SpaceX’s Crew Dragon spacecraft to safely and reliably dock with the International Space Station and other compatible orbital platforms.
  • F. None of above. chosen
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rendezvousTarget
Context triple: [Gemini 9A, rendezvousTarget, Augmented Target Docking Adapter]
  • A. rendezvousWith
    Indicates that two or more entities meet or come together at an agreed place and time, often for a specific purpose.
  • B. rendezvousType
    Indicates the specific kind or category of meeting or rendezvous that occurs between entities.
  • C. rendezvousProfile
    Indicates a relationship where entities coordinate to meet at a specific place and time, often under predefined conditions or plans.
  • D. rendezvousRole
    Indicates the specific function or capacity an entity assumes when participating in a rendezvous or planned meeting.
  • E. rendezvousAttemptResult
    Indicates the outcome or status of an attempt by entities to meet or rendezvous with each other.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d486e34819094a6c6ec26c047cf completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42e7176c819097e313ed8e8ceb06 completed April 3, 2026, 4:32 a.m.
NEDg Description generation batch_69cf43ead588819094089bea94c27207 completed April 3, 2026, 4:36 a.m.
NED2 Entity disambiguation (via description) batch_69cf453fa3e4819082466c59649c2f35 completed April 3, 2026, 4:42 a.m.
PD Predicate disambiguation batch_69cc457322b481908712a9630a17b954 completed March 31, 2026, 10:06 p.m.
PDg Predicate description generation batch_69cc572d99bc819097f36b140c2ee1ce completed March 31, 2026, 11:22 p.m.
Created at: March 30, 2026, 6:38 p.m.