Triple

T9271326
Position Surface form Disambiguated ID Type / Status
Subject Shahpura State E222834 entity
Predicate capital P234 FINISHED
Object Shahpura
Shahpura is a town in Rajasthan, India, historically known as the administrative and cultural center of the former princely Shahpura State.
 E798787 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: Shahpura | Statement: [Shahpura State, capital, Shahpura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shahpura
Context triple: [Shahpura State, capital, Shahpura]
  • A. Sikandarpur
    Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
  • B. Hoshangabad
    Hoshangabad is a city in the Indian state of Madhya Pradesh, known for its location on the banks of the Narmada River and its agricultural and industrial activities.
  • C. Sadulshahar
    Sadulshahar is a town in the northern Indian state of Rajasthan, situated within the Ganganagar district near the border with Punjab.
  • D. Rajanpur
    Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
  • E. Daryapur
    Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
  • 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: Shahpura
Triple: [Shahpura State, capital, Shahpura]
Generated description
Shahpura is a town in Rajasthan, India, historically known as the administrative and cultural center of the former princely Shahpura State.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shahpura
Target entity description: Shahpura is a town in Rajasthan, India, historically known as the administrative and cultural center of the former princely Shahpura State.
  • A. Sikandarpur
    Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
  • B. Hoshangabad
    Hoshangabad is a city in the Indian state of Madhya Pradesh, known for its location on the banks of the Narmada River and its agricultural and industrial activities.
  • C. Sadulshahar
    Sadulshahar is a town in the northern Indian state of Rajasthan, situated within the Ganganagar district near the border with Punjab.
  • D. Rajanpur
    Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
  • E. Daryapur
    Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
  • 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_69ca841ffe208190aa7bcffbef2f8379 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd07865790819099b3865a25dae58a completed April 1, 2026, 11:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1101359048190b37547d1fedb3bb1 completed April 4, 2026, 1:20 p.m.
NEDg Description generation batch_69d110ca72088190b9a65529801784a5 completed April 4, 2026, 1:23 p.m.
NED2 Entity disambiguation (via description) batch_69d1112224488190aeae685a1681539f completed April 4, 2026, 1:24 p.m.
Created at: March 30, 2026, 7:33 p.m.