Triple

T29610953
Position Surface form Disambiguated ID Type / Status
Subject Maharaja Brijendra Singh E754717 entity
Predicate name P16 FINISHED
Object Brijendra Singh
Brijendra Singh was an Indian royal figure who served as the Maharaja of Bharatpur in the mid-20th century.
E1898187 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: Brijendra Singh | Statement: [Maharaja Brijendra Singh, name, Brijendra Singh]
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: Brijendra Singh
Triple: [Maharaja Brijendra Singh, name, Brijendra Singh]
Generated description
Brijendra Singh was an Indian royal figure who served as the Maharaja of Bharatpur in the mid-20th century.

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_69f0ef85f62081909842b59fdf8717e1 completed April 28, 2026, 5:33 p.m.
NER Named-entity recognition batch_69f66deaf7ac8190b0be57d7f18d0c9b completed May 2, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2742f958708190b6173a49edb48281 completed June 8, 2026, 10:32 p.m.
NEDg Description generation batch_6a274413b51c8190a3c91c03d807114a completed June 8, 2026, 10:37 p.m.
NED2 Entity disambiguation (via description) batch_6a274457c73881909d77aa9da7d66e3d completed June 8, 2026, 10:38 p.m.
Created at: April 28, 2026, 6:28 p.m.