Triple

T29558987
Position Surface form Disambiguated ID Type / Status
Subject Muthal Mariyathai E749983 entity
Predicate leadActorRole P5563 FINISHED
Object Sivaji Ganesan as Malaichami
Sivaji Ganesan as Malaichami is the acclaimed portrayal of an elderly village chieftain whose poignant, understated performance is widely regarded as one of the finest of his career in Tamil cinema.
E1873854 NE FINISHED

How this triple was built (2 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: Sivaji Ganesan as Malaichami | Statement: [Muthal Mariyathai, leadActorRole, Sivaji Ganesan as Malaichami]
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: Sivaji Ganesan as Malaichami
Triple: [Muthal Mariyathai, leadActorRole, Sivaji Ganesan as Malaichami]
Generated description
Sivaji Ganesan as Malaichami is the acclaimed portrayal of an elderly village chieftain whose poignant, understated performance is widely regarded as one of the finest of his career in Tamil cinema.

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_69f0bd4919e48190942b2a13d5b97d03 completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66d1c12688190a93492438e18b74e completed May 2, 2026, 9:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a262d6376d4819087d1768896f38d34 completed June 8, 2026, 2:48 a.m.
NEDg Description generation batch_6a2631635b348190a628533ebaab1a6b completed June 8, 2026, 3:05 a.m.
NED2 Entity disambiguation (via description) batch_6a26358d611c8190904db2b471839ee3 completed June 8, 2026, 3:22 a.m.
Created at: April 28, 2026, 5:18 p.m.