Triple

T29120140
Position Surface form Disambiguated ID Type / Status
Subject Little Lost Robot E737156 entity
Predicate robotTypeFeatured P69082 FINISHED
Object NS-2 robot
The NS-2 robot is a fictional advanced robot model from Isaac Asimov’s “Little Lost Robot,” notable for having a modified version of the First Law of Robotics that makes it more dangerous and independent than standard robots.
 E1851830 NE FINISHED

How this triple was built (3 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: NS-2 robot | Statement: [Little Lost Robot, robotTypeFeatured, NS-2 robot]
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: NS-2 robot
Triple: [Little Lost Robot, robotTypeFeatured, NS-2 robot]
Generated description
The NS-2 robot is a fictional advanced robot model from Isaac Asimov’s “Little Lost Robot,” notable for having a modified version of the First Law of Robotics that makes it more dangerous and independent than standard robots.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: robotTypeFeatured
Context triple: [Little Lost Robot, robotTypeFeatured, NS-2 robot]
  • A. robotType
    Indicates the specific category or kind of robot that an entity belongs to.
  • B. featuresRobot chosen
    Indicates that something includes, presents, or prominently involves a robot as a key element or component.
  • C. robotFeature
    Indicates that a robot possesses or is characterized by a particular feature or attribute.
  • D. robotTypeDeveloped
    Indicates that a particular type or category of robot has been created or developed by an entity.
  • E. robotModelDesignation
    Indicates the specific model identifier or designation assigned to a robot.
  • F. None of above.

Provenance (6 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_69f077ed54e08190bb02a744e8121a66 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f661f3e9d48190bea96aeb602ab631 completed May 2, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2537ca9fd4819082b8559c2b00d38d completed June 7, 2026, 9:20 a.m.
NEDg Description generation batch_6a253bf87598819087116abf2274d649 completed June 7, 2026, 9:38 a.m.
NED2 Entity disambiguation (via description) batch_6a25470a98f48190b7afa02e39675cc3 completed June 7, 2026, 10:25 a.m.
PD Predicate disambiguation batch_69f65c2376a08190be5215171e908e69 completed May 2, 2026, 8:18 p.m.
Created at: April 28, 2026, 11:25 a.m.