Triple

T3341351
Position Surface form Disambiguated ID Type / Status
Subject Cyberabad E70266 entity
Predicate hasArea P175 FINISHED
Object Nanakramguda
Nanakramguda is a prominent IT and financial district in Hyderabad, India, known for housing major technology parks, corporate offices, and the city’s financial services hub.
E350661 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: Nanakramguda | Statement: [Cyberabad, hasArea, Nanakramguda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nanakramguda
Context triple: [Cyberabad, hasArea, Nanakramguda]
  • A. Palamoor
    Palamoor is the historical name of Mahbubnagar, a town and district headquarters in the Indian state of Telangana.
  • B. Gannavaram
    Gannavaram is a suburban town near Vijayawada in Andhra Pradesh, India, known primarily for hosting the city's main airport.
  • C. Vikrampura
    Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
  • D. Sullurpeta
    Sullurpeta is a town in Andhra Pradesh, India, known primarily for its proximity to India’s premier spaceport, the Satish Dhawan Space Centre at Sriharikota.
  • E. Kanchrapara
    Kanchrapara is a town in the North 24 Parganas district of West Bengal, India, known historically for its railway workshop and suburban connectivity to Kolkata.
  • 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: Nanakramguda
Triple: [Cyberabad, hasArea, Nanakramguda]
Generated description
Nanakramguda is a prominent IT and financial district in Hyderabad, India, known for housing major technology parks, corporate offices, and the city’s financial services hub.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nanakramguda
Target entity description: Nanakramguda is a prominent IT and financial district in Hyderabad, India, known for housing major technology parks, corporate offices, and the city’s financial services hub.
  • A. Palamoor
    Palamoor is the historical name of Mahbubnagar, a town and district headquarters in the Indian state of Telangana.
  • B. Gannavaram
    Gannavaram is a suburban town near Vijayawada in Andhra Pradesh, India, known primarily for hosting the city's main airport.
  • C. Vikrampura
    Vikrampura was an important historical city that served as a principal royal center of the medieval Indian Pala dynasty in eastern India.
  • D. Sullurpeta
    Sullurpeta is a town in Andhra Pradesh, India, known primarily for its proximity to India’s premier spaceport, the Satish Dhawan Space Centre at Sriharikota.
  • E. Kanchrapara
    Kanchrapara is a town in the North 24 Parganas district of West Bengal, India, known historically for its railway workshop and suburban connectivity to Kolkata.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1c0ae44819091c851569eaf4565 completed March 8, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b325191a38819095cdccca8f013774 completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b3264fee388190a693ecf748074f04 completed March 12, 2026, 8:47 p.m.
NED2 Entity disambiguation (via description) batch_69b326af5e1481908930410ce9be1339 completed March 12, 2026, 8:48 p.m.
Created at: March 8, 2026, 3:12 p.m.