Triple

T29593758
Position Surface form Disambiguated ID Type / Status
Subject Gautham Vasudev Menon E754237 entity
Predicate notableWork P4 FINISHED
Object Enai Noki Paayum Thota
Enai Noki Paayum Thota is a Tamil-language romantic thriller film directed by Gautham Vasudev Menon, known for its intense love story, stylish action, and prominent music.
E1877799 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: Enai Noki Paayum Thota | Statement: [Gautham Vasudev Menon, notableWork, Enai Noki Paayum Thota]
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: Enai Noki Paayum Thota
Triple: [Gautham Vasudev Menon, notableWork, Enai Noki Paayum Thota]
Generated description
Enai Noki Paayum Thota is a Tamil-language romantic thriller film directed by Gautham Vasudev Menon, known for its intense love story, stylish action, and prominent music.

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_69f0ef836ac88190bd809dc58b5ec907 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66db5b6fc81908d5b3bdbb085a93d completed May 2, 2026, 9:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26615fe350819085fe9656f140edaf completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a26658b86e88190b68b3a7d183a72e9 completed June 8, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a266c326a7081909d55ff20b5c3b851 completed June 8, 2026, 7:16 a.m.
Created at: April 28, 2026, 6:16 p.m.