Triple

T3467235
Position Surface form Disambiguated ID Type / Status
Subject Patel E73166 entity
Predicate hasNotableBearer P458 FINISHED
Object Sanjay Patel
Sanjay Patel is a common Indian name shared by several notable individuals, including professionals in fields such as animation, business, and academia.
E364240 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: Sanjay Patel | Statement: [Patel, hasNotableBearer, Sanjay Patel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanjay Patel
Context triple: [Patel, hasNotableBearer, Sanjay Patel]
  • A. Kumar Patel
    Kumar Patel is a laid-back, marijuana-loving Korean American character from the "Harold & Kumar" comedy film series, known for his misadventurous escapades with his best friend Harold Lee.
  • B. Sanjay Jain
    Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
  • C. Rasesh Bhatt
    Rasesh Bhatt is known primarily as the husband of renowned Indian cooperative organizer and SEWA founder Ela Bhatt.
  • D. Jhaverba Patel
    Jhaverba Patel was the wife of Sardar Vallabhbhai Patel, a key leader of the Indian independence movement and India’s first Deputy Prime Minister.
  • E. Amin Bhatia
    Amin Bhatia is a Canadian composer and synthesist known for his cinematic electronic scores for film and television.
  • 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: Sanjay Patel
Triple: [Patel, hasNotableBearer, Sanjay Patel]
Generated description
Sanjay Patel is a common Indian name shared by several notable individuals, including professionals in fields such as animation, business, and academia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sanjay Patel
Target entity description: Sanjay Patel is a common Indian name shared by several notable individuals, including professionals in fields such as animation, business, and academia.
  • A. Kumar Patel
    Kumar Patel is a laid-back, marijuana-loving Korean American character from the "Harold & Kumar" comedy film series, known for his misadventurous escapades with his best friend Harold Lee.
  • B. Sanjay Jain
    Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
  • C. Rasesh Bhatt
    Rasesh Bhatt is known primarily as the husband of renowned Indian cooperative organizer and SEWA founder Ela Bhatt.
  • D. Jhaverba Patel
    Jhaverba Patel was the wife of Sardar Vallabhbhai Patel, a key leader of the Indian independence movement and India’s first Deputy Prime Minister.
  • E. Amin Bhatia
    Amin Bhatia is a Canadian composer and synthesist known for his cinematic electronic scores for film and television.
  • 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_69ad85b224d481908ff8be51338d24ff completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbb1090188190ac8aafd87dfaa6a7 completed March 8, 2026, 6:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e5c1f008190b1351e3d3e53fc11 completed March 13, 2026, 3:02 a.m.
NEDg Description generation batch_69b37ea9c1308190a307b8de9beb0012 completed March 13, 2026, 3:04 a.m.
NED2 Entity disambiguation (via description) batch_69b37ef9babc8190847b29af9cdc1006 completed March 13, 2026, 3:05 a.m.
Created at: March 8, 2026, 3:17 p.m.