Triple

T8558926
Position Surface form Disambiguated ID Type / Status
Subject Roja E202642 entity
Predicate editedBy P1954 FINISHED
Object Suresh Urs
Suresh Urs is an acclaimed Indian film editor known for his work on numerous prominent Kannada, Tamil, and Hindi films.
E746027 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: Suresh Urs | Statement: [Roja, editedBy, Suresh Urs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Suresh Urs
Context triple: [Roja, editedBy, Suresh Urs]
  • A. Shankar Patil
    Shankar Patil is a prominent Marathi playwright known for his influential contributions to contemporary Marathi theatre.
  • B. Shripad Naik
    Shripad Naik is an Indian politician and long-serving Member of Parliament from Goa who has held multiple ministerial roles in the central government.
  • C. Manohar Raju
    Manohar Raju is an American attorney and criminal justice reform advocate who serves as the elected Public Defender of San Francisco.
  • D. Nagendra Babu
    Nagendra Babu is an Indian film actor and producer primarily associated with Telugu cinema and the influential Konidela family film dynasty.
  • E. Raghuveer Chaudhari
    Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
  • 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: Suresh Urs
Triple: [Roja, editedBy, Suresh Urs]
Generated description
Suresh Urs is an acclaimed Indian film editor known for his work on numerous prominent Kannada, Tamil, and Hindi films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Suresh Urs
Target entity description: Suresh Urs is an acclaimed Indian film editor known for his work on numerous prominent Kannada, Tamil, and Hindi films.
  • A. Shankar Patil
    Shankar Patil is a prominent Marathi playwright known for his influential contributions to contemporary Marathi theatre.
  • B. Shripad Naik
    Shripad Naik is an Indian politician and long-serving Member of Parliament from Goa who has held multiple ministerial roles in the central government.
  • C. Manohar Raju
    Manohar Raju is an American attorney and criminal justice reform advocate who serves as the elected Public Defender of San Francisco.
  • D. Nagendra Babu
    Nagendra Babu is an Indian film actor and producer primarily associated with Telugu cinema and the influential Konidela family film dynasty.
  • E. Raghuveer Chaudhari
    Raghuveer Chaudhari is an acclaimed Indian Gujarati writer and scholar renowned for his influential novels, poetry, and literary criticism.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9485dd88190bc2cf2adf39d48ee completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea871dd3081908e24c4d1c60a8381 completed April 2, 2026, 5:33 p.m.
NEDg Description generation batch_69cea996a5c48190a12ffe8e282d2d9c completed April 2, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69ceadb2d52c8190aada1d797753663e completed April 2, 2026, 5:56 p.m.
Created at: March 30, 2026, 6:20 p.m.