Triple

T8667403
Position Surface form Disambiguated ID Type / Status
Subject Sivaji Ganesan E205710 entity
Predicate notableWork P4 FINISHED
Object Deiva Magan
Deiva Magan is a 1969 Tamil-language drama film renowned for Sivaji Ganesan’s acclaimed triple-role performance and its emotionally intense storyline.
E749955 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: Deiva Magan | Statement: [Sivaji Ganesan, notableWork, Deiva Magan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Deiva Magan
Context triple: [Sivaji Ganesan, notableWork, Deiva Magan]
  • A. Magan
    Magan was an ancient Bronze Age region, likely in present-day Oman or the surrounding Arabian Peninsula, known as a key maritime trading partner of the Indus Valley Civilization and Mesopotamia.
  • B. Majgull
    Majgull is a Swedish given name, notably borne by the acclaimed author Majgull Axelsson.
  • C. La Dea
    La Dea is the widely used nickname for Italian football club Atalanta Bergamasca Calcio, referencing the mythological goddess Atalanta.
  • D. Jadu
    Jadu is a small town in western Libya situated in the Nafusa Mountains, known for its Amazigh (Berber) heritage and strategic highland location.
  • E. Nedmag
    Nedmag is a Dutch company specializing in the production of high-quality magnesium salts and related mineral products.
  • 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: Deiva Magan
Triple: [Sivaji Ganesan, notableWork, Deiva Magan]
Generated description
Deiva Magan is a 1969 Tamil-language drama film renowned for Sivaji Ganesan’s acclaimed triple-role performance and its emotionally intense storyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Deiva Magan
Target entity description: Deiva Magan is a 1969 Tamil-language drama film renowned for Sivaji Ganesan’s acclaimed triple-role performance and its emotionally intense storyline.
  • A. Magan
    Magan was an ancient Bronze Age region, likely in present-day Oman or the surrounding Arabian Peninsula, known as a key maritime trading partner of the Indus Valley Civilization and Mesopotamia.
  • B. Majgull
    Majgull is a Swedish given name, notably borne by the acclaimed author Majgull Axelsson.
  • C. La Dea
    La Dea is the widely used nickname for Italian football club Atalanta Bergamasca Calcio, referencing the mythological goddess Atalanta.
  • D. Jadu
    Jadu is a small town in western Libya situated in the Nafusa Mountains, known for its Amazigh (Berber) heritage and strategic highland location.
  • E. Nedmag
    Nedmag is a Dutch company specializing in the production of high-quality magnesium salts and related mineral products.
  • 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_69ca83516ae88190aefe034b3bc589e3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc48a34b808190aa9aed9cdb2900e6 completed March 31, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd1ca88c8190a3b2ca79a7204248 completed April 2, 2026, 8:10 p.m.
NEDg Description generation batch_69cece8fcbcc8190832a66287bc8f833 completed April 2, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_69cecff48600819086a15700cb947056 completed April 2, 2026, 8:22 p.m.
Created at: March 30, 2026, 6:31 p.m.