Triple

T29610911
Position Surface form Disambiguated ID Type / Status
Subject Sinsinwar Jat dynasty E754716 entity
Predicate founder P104 FINISHED
Object Badan Singh
Badan Singh was an 18th-century Jat ruler best known for establishing the princely state of Bharatpur in northern India.
E1877172 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: Badan Singh | Statement: [Sinsinwar Jat dynasty, founder, Badan 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: Badan Singh
Triple: [Sinsinwar Jat dynasty, founder, Badan Singh]
Generated description
Badan Singh was an 18th-century Jat ruler best known for establishing the princely state of Bharatpur in northern India.

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_6a2661643af8819093679b3e91932a42 completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a2665a18cdc819085edf38c5b97f863 completed June 8, 2026, 6:48 a.m.
NED2 Entity disambiguation (via description) batch_6a266b5c5f308190a49fa8399a76ad96 completed June 8, 2026, 7:12 a.m.
Created at: April 28, 2026, 6:28 p.m.