Triple

T29499101
Position Surface form Disambiguated ID Type / Status
Subject Andha Naal E748317 entity
Predicate director P255 FINISHED
Object S. Balachander
S. Balachander was an Indian veena virtuoso, actor, and filmmaker known for his innovative contributions to Carnatic music and Tamil cinema.
E2014011 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: S. Balachander | Statement: [Andha Naal, director, S. Balachander]
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: S. Balachander
Triple: [Andha Naal, director, S. Balachander]
Generated description
S. Balachander was an Indian veena virtuoso, actor, and filmmaker known for his innovative contributions to Carnatic music and 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_69f0bd455a9c8190b40a3e8ea38cf61f completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c3129508190aa6bbd520f4daea6 completed May 2, 2026, 9:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3485e4bafc8190b09c53f0727c836c completed June 18, 2026, 11:57 p.m.
NEDg Description generation batch_6a3487730848819093ffdd72872b0131 completed June 19, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_6a3487efeb248190b0d48dc5266c3927 completed June 19, 2026, 12:06 a.m.
Created at: April 28, 2026, 4:21 p.m.