Triple

T871192
Position Surface form Disambiguated ID Type / Status
Subject Sebastian Thrun E18816 entity
Predicate familyName P18 FINISHED
Object Thrun
Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
 E102289 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: Thrun | Statement: [Sebastian Thrun, familyName, Thrun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Thrun
Context triple: [Sebastian Thrun, familyName, Thrun]
  • A. Watson
    Watson is a common English surname borne by numerous notable figures, including scientists, artists, and public personalities.
  • B. Cozmo
    Cozmo is the playful, costumed alien mascot of Major League Soccer club LA Galaxy, known for entertaining fans at matches and team events.
  • C. WATSON
    WATSON is a close-up imaging camera on NASA’s Perseverance rover used to examine the fine details of Martian rocks and surface materials.
  • D. Brin
    Brin is a surname most prominently associated with Sergey Brin, the co-founder of Google and a leading figure in the technology industry.
  • E. Dextre
    Dextre is a two-armed robotic handyman on the International Space Station designed to perform delicate maintenance tasks and reduce the need for spacewalks.
  • 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: Thrun
Triple: [Sebastian Thrun, familyName, Thrun]
Generated description
Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Thrun
Target entity description: Thrun is the surname of Sebastian Thrun, a prominent computer scientist and robotics expert known for his work in self-driving cars and artificial intelligence.
  • A. Watson
    Watson is a common English surname borne by numerous notable figures, including scientists, artists, and public personalities.
  • B. Cozmo
    Cozmo is the playful, costumed alien mascot of Major League Soccer club LA Galaxy, known for entertaining fans at matches and team events.
  • C. WATSON
    WATSON is a close-up imaging camera on NASA’s Perseverance rover used to examine the fine details of Martian rocks and surface materials.
  • D. Brin
    Brin is a surname most prominently associated with Sergey Brin, the co-founder of Google and a leading figure in the technology industry.
  • E. Dextre
    Dextre is a two-armed robotic handyman on the International Space Station designed to perform delicate maintenance tasks and reduce the need for spacewalks.
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac94d5ac81909feee876696da589 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3cb9a648190981182add42325f3 completed March 4, 2026, 3:15 a.m.
NEDg Description generation batch_69a7a558c1308190810a139ad24dfc9d completed March 4, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a7a5e744188190ae30544753fb9399 completed March 4, 2026, 3:24 a.m.
Created at: March 1, 2026, 7:39 p.m.