Triple

T11589257
Position Surface form Disambiguated ID Type / Status
Subject Khargone district E274834 entity
Predicate containsTown P847 FINISHED
Object Mandleshwar
Mandleshwar is a historic town on the banks of the Narmada River in Madhya Pradesh, India, known for its temples and scenic ghats.
 E941375 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: Mandleshwar | Statement: [Khargone district, containsTown, Mandleshwar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mandleshwar
Context triple: [Khargone district, containsTown, Mandleshwar]
  • A. Jagdishpur
    Jagdishpur is a town in the Bhojpur district of Bihar, India, historically known as the ancestral estate of the 19th-century freedom fighter Kunwar Singh.
  • B. Bhopalgarh
    Bhopalgarh is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the region.
  • C. Chandanpura
    Chandanpura is a locality in Chittagong, Bangladesh, known for its historic architecture and urban commercial activity.
  • D. Laxmangarh
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
  • E. Laxmangarh
    Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
  • 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: Mandleshwar
Triple: [Khargone district, containsTown, Mandleshwar]
Generated description
Mandleshwar is a historic town on the banks of the Narmada River in Madhya Pradesh, India, known for its temples and scenic ghats.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mandleshwar
Target entity description: Mandleshwar is a historic town on the banks of the Narmada River in Madhya Pradesh, India, known for its temples and scenic ghats.
  • A. Jagdishpur
    Jagdishpur is a town in the Bhojpur district of Bihar, India, historically known as the ancestral estate of the 19th-century freedom fighter Kunwar Singh.
  • B. Bhopalgarh
    Bhopalgarh is a town in the Indian state of Rajasthan, known for its rural setting and administrative role within the region.
  • C. Chandanpura
    Chandanpura is a locality in Chittagong, Bangladesh, known for its historic architecture and urban commercial activity.
  • D. Laxmangarh
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
  • E. Laxmangarh
    Laxmangarh is a town in the Alwar district of Rajasthan, India, known for its local markets and surrounding agricultural communities.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d89463360c8190b91228c46bfe2e5f completed April 10, 2026, 6:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef8269c4f48190aaf238a64c5caf1d completed April 27, 2026, 3:36 p.m.
NEDg Description generation batch_69ef96ab29d48190b225504856007384 completed April 27, 2026, 5:02 p.m.
NED2 Entity disambiguation (via description) batch_69efd64bfa7081909715aa64d80fadf3 completed April 27, 2026, 9:34 p.m.
Created at: April 8, 2026, 9:38 p.m.