Triple

T6228018
Position Surface form Disambiguated ID Type / Status
Subject Kalinga E139282 entity
Predicate capital P234 FINISHED
Object Dantapura
Dantapura was an ancient city traditionally identified as the royal and administrative center of the Kalinga kingdom in eastern India.
 E583273 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: Dantapura | Statement: [Kalinga, capital, Dantapura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dantapura
Context triple: [Kalinga, capital, Dantapura]
  • A. Tuljapur
    Tuljapur is a town in Maharashtra, India, renowned as a major pilgrimage center for the goddess Bhavani.
  • B. Dahanapura
    Dahanapura was the principal city and political center of the historical Kediri Kingdom in Java.
  • C. 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.
  • D. Khandala
    Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
  • E. Sri Madhopur
    Sri Madhopur is a town in the Sikar district of Rajasthan, India, known for its historical significance and regional trade and agriculture.
  • 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: Dantapura
Triple: [Kalinga, capital, Dantapura]
Generated description
Dantapura was an ancient city traditionally identified as the royal and administrative center of the Kalinga kingdom in eastern India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dantapura
Target entity description: Dantapura was an ancient city traditionally identified as the royal and administrative center of the Kalinga kingdom in eastern India.
  • A. Tuljapur
    Tuljapur is a town in Maharashtra, India, renowned as a major pilgrimage center for the goddess Bhavani.
  • B. Dahanapura
    Dahanapura was the principal city and political center of the historical Kediri Kingdom in Java.
  • C. 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.
  • D. Khandala
    Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
  • E. Sri Madhopur
    Sri Madhopur is a town in the Sikar district of Rajasthan, India, known for its historical significance and regional trade and agriculture.
  • 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_69c008afd3148190b71e9eaa60420dd1 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062d686b88190a0e7e38ab52e2d4a completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3e5bd988190ad9b0af668f5b05c completed March 27, 2026, 1:56 a.m.
NEDg Description generation batch_69c5e531074481909f2b9099857d7414 completed March 27, 2026, 2:02 a.m.
NED2 Entity disambiguation (via description) batch_69c5e58034888190bd24310eff354633 completed March 27, 2026, 2:03 a.m.
Created at: March 22, 2026, 4:22 p.m.