Triple

T13061684
Position Surface form Disambiguated ID Type / Status
Subject Nandan Nilekani E329212 entity
Predicate givenName P17 FINISHED
Object Nandan
Nandan is the first name of Nandan Nilekani, the Indian entrepreneur, co-founder of Infosys, and former chairman of the Unique Identification Authority of India (UIDAI).
E1017387 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: Nandan | Statement: [Nandan Nilekani, givenName, Nandan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nandan
Context triple: [Nandan Nilekani, givenName, Nandan]
  • A. Nandiraj
    Nandiraj is a tributary river that feeds into the Indravati River in central India.
  • B. Nanddas
    Nanddas was a prominent 16th-century devotional poet of the Pushtimarg tradition, celebrated for his Braj-language compositions praising Krishna.
  • C. Bhanu
    Bhanu is a locality in the Indian state of Haryana known for hosting the Basic Training Centre, a key military training facility.
  • D. Biraj Bou
    Biraj Bou is a classic Bengali novel by Sarat Chandra Chattopadhyay that explores the struggles, dignity, and emotional life of a devoted wife in a traditional Indian household.
  • E. Nandha
    Nandha is a 2001 Tamil-language drama film directed by Bala, widely recognized for Suriya’s breakthrough performance in a gritty, emotionally intense role.
  • 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: Nandan
Triple: [Nandan Nilekani, givenName, Nandan]
Generated description
Nandan is the first name of Nandan Nilekani, the Indian entrepreneur, co-founder of Infosys, and former chairman of the Unique Identification Authority of India (UIDAI).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nandan
Target entity description: Nandan is the first name of Nandan Nilekani, the Indian entrepreneur, co-founder of Infosys, and former chairman of the Unique Identification Authority of India (UIDAI).
  • A. Nandiraj
    Nandiraj is a tributary river that feeds into the Indravati River in central India.
  • B. Nanddas
    Nanddas was a prominent 16th-century devotional poet of the Pushtimarg tradition, celebrated for his Braj-language compositions praising Krishna.
  • C. Bhanu
    Bhanu is a locality in the Indian state of Haryana known for hosting the Basic Training Centre, a key military training facility.
  • D. Biraj Bou
    Biraj Bou is a classic Bengali novel by Sarat Chandra Chattopadhyay that explores the struggles, dignity, and emotional life of a devoted wife in a traditional Indian household.
  • E. Nandha
    Nandha is a 2001 Tamil-language drama film directed by Bala, widely recognized for Suriya’s breakthrough performance in a gritty, emotionally intense role.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980e7ee548190b4b18bdb1357c359 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbe45c8c819080fbdf1d94376feb completed May 3, 2026, 4:15 a.m.
NEDg Description generation batch_69f6cd3d5090819091b65f544ad139fd completed May 3, 2026, 4:21 a.m.
NED2 Entity disambiguation (via description) batch_69f6cdc8d52c819083717a455d589646 completed May 3, 2026, 4:23 a.m.
Created at: April 9, 2026, 8:59 p.m.