Triple

T29332669
Position Surface form Disambiguated ID Type / Status
Subject Kadalikka Neramillai E743820 entity
Predicate director P255 FINISHED
Object C. V. Sridhar
C. V. Sridhar was a prominent Indian film director and screenwriter known for his influential work in Tamil cinema, particularly in romantic comedies and dramas from the 1950s to the 1970s.
 E1999712 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: C. V. Sridhar | Statement: [Kadalikka Neramillai, director, C. V. Sridhar]
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: C. V. Sridhar
Triple: [Kadalikka Neramillai, director, C. V. Sridhar]
Generated description
C. V. Sridhar was a prominent Indian film director and screenwriter known for his influential work in Tamil cinema, particularly in romantic comedies and dramas from the 1950s to the 1970s.

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_69f09126cfcc8190899b16fbf3c2bf7b completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f6689bdf748190ae27cdae897bc6b3 completed May 2, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2f46ab264c8190971e9be54df04f95 completed June 15, 2026, 12:26 a.m.
NEDg Description generation batch_6a2f48ed53d081909c9b26a5303fbc54 completed June 15, 2026, 12:35 a.m.
NED2 Entity disambiguation (via description) batch_6a2f4940fc2481909cd539b134f08560 completed June 15, 2026, 12:37 a.m.
Created at: April 28, 2026, 1:30 p.m.