Triple

T9497973
Position Surface form Disambiguated ID Type / Status
Subject Malwa Plateau E229058 entity
Predicate containsCity P294 FINISHED
Object Nagda
Nagda is an industrial town in the Indian state of Madhya Pradesh, known especially for its large textile and chemical manufacturing units.
 E803624 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: Nagda | Statement: [Malwa Plateau, containsCity, Nagda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nagda
Context triple: [Malwa Plateau, containsCity, Nagda]
  • A. Narnaund
    Narnaund is a prominent town in the northern Indian state of Haryana, known for its agricultural economy and role as a local commercial hub.
  • B. Rupnagar
    Rupnagar is a historic town in the Indian state of Punjab, known as one of the earliest Indus Valley Civilization sites and an important regional administrative and cultural center.
  • C. Chandanpura
    Chandanpura is a locality in Chittagong, Bangladesh, known for its historic architecture and urban commercial activity.
  • D. Nategaon
    Nategaon is a village in India known primarily as the birthplace of prominent Indian civil servant and economist C. D. Deshmukh.
  • E. Sohagpur
    Sohagpur is a town in the Narmadapuram district of Madhya Pradesh, India, known as a local commercial center and access point to nearby forested and wildlife areas.
  • 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: Nagda
Triple: [Malwa Plateau, containsCity, Nagda]
Generated description
Nagda is an industrial town in the Indian state of Madhya Pradesh, known especially for its large textile and chemical manufacturing units.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nagda
Target entity description: Nagda is an industrial town in the Indian state of Madhya Pradesh, known especially for its large textile and chemical manufacturing units.
  • A. Narnaund
    Narnaund is a prominent town in the northern Indian state of Haryana, known for its agricultural economy and role as a local commercial hub.
  • B. Rupnagar
    Rupnagar is a historic town in the Indian state of Punjab, known as one of the earliest Indus Valley Civilization sites and an important regional administrative and cultural center.
  • C. Chandanpura
    Chandanpura is a locality in Chittagong, Bangladesh, known for its historic architecture and urban commercial activity.
  • D. Nategaon
    Nategaon is a village in India known primarily as the birthplace of prominent Indian civil servant and economist C. D. Deshmukh.
  • E. Sohagpur
    Sohagpur is a town in the Narmadapuram district of Madhya Pradesh, India, known as a local commercial center and access point to nearby forested and wildlife areas.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95ef06b88190b7a840caddea3e38 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a0a5ec881908bb1643d2bea2c9f completed April 4, 2026, 4:19 p.m.
NEDg Description generation batch_69d13b7752fc819094ceb0ade960ecad completed April 4, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_69d13bc9f0dc8190879c37383b197a3b completed April 4, 2026, 4:26 p.m.
Created at: March 30, 2026, 7:56 p.m.