Triple

T26135809
Position Surface form Disambiguated ID Type / Status
Subject Adbhut Ramayana (Assamese adaptation) E659377 entity
Predicate hasMainDeity P7648 FINISHED
Object Rama
Rama is a major Hindu deity revered as the virtuous prince and seventh avatar of Vishnu, celebrated primarily through the epic Ramayana.
E103308 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: Rama | Statement: [Adbhut Ramayana (Assamese adaptation), hasMainDeity, Rama]
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: Rama
Triple: [Adbhut Ramayana (Assamese adaptation), hasMainDeity, Rama]
Generated description
Rama is a major Hindu deity revered as the virtuous prince and seventh avatar of Vishnu, celebrated primarily through the epic Ramayana.

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_69ee5bc3c20c8190bf2cf272f4170e95 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f60b96c1ac8190adc0ceb44507777e completed May 2, 2026, 2:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a112764acb48190b45949a5d16d5234 completed May 23, 2026, 4:04 a.m.
NEDg Description generation batch_6a1134849eac8190a0f80898df1ae20c completed May 23, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_6a11350decb88190b61a8491db612650 completed May 23, 2026, 5:03 a.m.
Created at: April 26, 2026, 8:17 p.m.