Triple

T34699644
Position Surface form Disambiguated ID Type / Status
Subject Ratan Singh I E1000329 entity
Predicate associatedWith P37 FINISHED
Object Chittor kingdom
The Chittor kingdom was a historic Rajput realm in present-day Rajasthan, India, centered on the formidable hill-fort of Chittorgarh and renowned for its fierce resistance against repeated invasions.
E2109252 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: Chittor kingdom | Statement: [Ratan Singh I, associatedWith, Chittor kingdom]
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: Chittor kingdom
Triple: [Ratan Singh I, associatedWith, Chittor kingdom]
Generated description
The Chittor kingdom was a historic Rajput realm in present-day Rajasthan, India, centered on the formidable hill-fort of Chittorgarh and renowned for its fierce resistance against repeated invasions.

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_69f76dab937881909c86f1b9ad50445f completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f7796f2de881909e3ee00e11f15612 completed May 3, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a375bdafd94819089e320c59afc2808 completed June 21, 2026, 3:34 a.m.
NEDg Description generation batch_6a375cb7df048190b0c786ee76dec1bc completed June 21, 2026, 3:38 a.m.
NED2 Entity disambiguation (via description) batch_6a375d2cf03c819098514298e41adbe7 completed June 21, 2026, 3:40 a.m.
Created at: May 3, 2026, 3:59 p.m.