Triple

T7523865
Position Surface form Disambiguated ID Type / Status
Subject STS-90 E177842 entity
Predicate missionName P10665 FINISHED
Object Neurolab
Neurolab was a 1998 Space Shuttle STS-90 mission dedicated to studying how microgravity affects the nervous system and brain function in humans and animals.
E670785 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: Neurolab | Statement: [STS-90, missionName, Neurolab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neurolab
Context triple: [STS-90, missionName, Neurolab]
  • A. Perceptrons
    Perceptrons is a seminal 1969 book by Marvin Minsky and Seymour Papert that critically analyzes the capabilities and limitations of early neural network models, profoundly influencing the development of artificial intelligence and machine learning.
  • B. Cascade-Correlation learning architecture
    Cascade-Correlation learning architecture is a neural network training method that incrementally builds its own topology by adding new hidden units during learning to improve performance.
  • C. Hopfield networks
    Hopfield networks are recurrent artificial neural networks that serve as content-addressable memory systems, storing patterns as stable states and retrieving them through dynamics that minimize an energy function.
  • D. RBM
    RBM is a global partnership initiative dedicated to coordinating and scaling up efforts to prevent, control, and ultimately eliminate malaria worldwide.
  • E. Hebbian learning
    Hebbian learning is a neurobiological and computational learning principle often summarized as "cells that fire together wire together," where the connection between neurons is strengthened when they are activated simultaneously.
  • 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: Neurolab
Triple: [STS-90, missionName, Neurolab]
Generated description
Neurolab was a 1998 Space Shuttle STS-90 mission dedicated to studying how microgravity affects the nervous system and brain function in humans and animals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Neurolab
Target entity description: Neurolab was a 1998 Space Shuttle STS-90 mission dedicated to studying how microgravity affects the nervous system and brain function in humans and animals.
  • A. Perceptrons
    Perceptrons is a seminal 1969 book by Marvin Minsky and Seymour Papert that critically analyzes the capabilities and limitations of early neural network models, profoundly influencing the development of artificial intelligence and machine learning.
  • B. Cascade-Correlation learning architecture
    Cascade-Correlation learning architecture is a neural network training method that incrementally builds its own topology by adding new hidden units during learning to improve performance.
  • C. Hopfield networks
    Hopfield networks are recurrent artificial neural networks that serve as content-addressable memory systems, storing patterns as stable states and retrieving them through dynamics that minimize an energy function.
  • D. RBM
    RBM is a global partnership initiative dedicated to coordinating and scaling up efforts to prevent, control, and ultimately eliminate malaria worldwide.
  • E. Hebbian learning
    Hebbian learning is a neurobiological and computational learning principle often summarized as "cells that fire together wire together," where the connection between neurons is strengthened when they are activated simultaneously.
  • 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_69c69f29bf3081909a146aec7755f185 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f7c61b508190b582f54ecbb387e3 completed March 27, 2026, 9:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84631e6bc819099b3a7819c3ae9a7 completed March 28, 2026, 9:20 p.m.
NEDg Description generation batch_69c8471e50ec8190b3d9e9fa5212cbac completed March 28, 2026, 9:24 p.m.
NED2 Entity disambiguation (via description) batch_69c8478782388190bb0e86bfb455750b completed March 28, 2026, 9:26 p.m.
Created at: March 27, 2026, 3:46 p.m.