Triple

T34504046
Position Surface form Disambiguated ID Type / Status
Subject Videha dynasty E885833 entity
Predicate associatedWithFigure P1183 FINISHED
Object Rama
Rama is a major deity in Hinduism and the virtuous prince-king hero of the epic Ramayana, revered as an avatar of the god Vishnu.
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: [Videha dynasty, associatedWithFigure, 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: [Videha dynasty, associatedWithFigure, Rama]
Generated description
Rama is a major deity in Hinduism and the virtuous prince-king hero of the epic Ramayana, revered as an avatar of the god Vishnu.

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_69f349cc0220819081f154c6964f4dc2 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71f5505e48190a937829310619fcb completed May 3, 2026, 10:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37214920588190aca778c57f4b74f8 completed June 20, 2026, 11:24 p.m.
NEDg Description generation batch_6a3723380cf88190a60af48ee1a87afd completed June 20, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_6a37238ff5d0819083b6316745d9de61 completed June 20, 2026, 11:34 p.m.
Created at: May 1, 2026, 2:01 a.m.