Triple

T364248
Position Surface form Disambiguated ID Type / Status
Subject Google Brain E7923 entity
Predicate notableMember P10 FINISHED
Object Rajat Monga
Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
E46145 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: Rajat Monga | Statement: [Google Brain, notableMember, Rajat Monga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rajat Monga
Context triple: [Google Brain, notableMember, Rajat Monga]
  • A. Neal Mohan
    Neal Mohan is an Indian-American technology executive and digital advertising expert who serves as the CEO of YouTube.
  • B. D. Udaya Kumar
    D. Udaya Kumar is an Indian academic and designer best known for creating the modern symbol of the Indian rupee currency.
  • C. Shadharwan
    Shadharwan is the sloped stone base or foundation that runs along the lower exterior walls of the Kaaba in Mecca.
  • D. Partha
    Partha is a given name commonly used in India, often associated with figures in academia, arts, and public life.
  • E. Monika Mann
    Monika Mann was a German writer and essayist, best known as one of the literary Nobel laureate Thomas Mann’s daughters and a member of the prominent Mann family of intellectuals.
  • 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: Rajat Monga
Triple: [Google Brain, notableMember, Rajat Monga]
Generated description
Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rajat Monga
Target entity description: Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
  • A. Neal Mohan
    Neal Mohan is an Indian-American technology executive and digital advertising expert who serves as the CEO of YouTube.
  • B. D. Udaya Kumar
    D. Udaya Kumar is an Indian academic and designer best known for creating the modern symbol of the Indian rupee currency.
  • C. Shadharwan
    Shadharwan is the sloped stone base or foundation that runs along the lower exterior walls of the Kaaba in Mecca.
  • D. Partha
    Partha is a given name commonly used in India, often associated with figures in academia, arts, and public life.
  • E. Monika Mann
    Monika Mann was a German writer and essayist, best known as one of the literary Nobel laureate Thomas Mann’s daughters and a member of the prominent Mann family of intellectuals.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebd1016481909b8ba3b047a47145 completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e86533a481909bab5f0b52114c6a completed March 1, 2026, 7:19 a.m.
NEDg Description generation batch_69a3e99fd210819099e83cd183a4daa7 completed March 1, 2026, 7:24 a.m.
NED2 Entity disambiguation (via description) batch_69a3ea45c86c8190a6c215430601ad15 completed March 1, 2026, 7:27 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.