Triple

T26142777
Position Surface form Disambiguated ID Type / Status
Subject Hindu College, Calcutta E659565 entity
Predicate foundedBy P104 FINISHED
Object Gopi Mohan Deb
Gopi Mohan Deb was a prominent 19th-century Bengali zamindar and philanthropist known for his significant contributions to education and public institutions in colonial Calcutta.
E1865184 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: Gopi Mohan Deb | Statement: [Hindu College, Calcutta, foundedBy, Gopi Mohan Deb]
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: Gopi Mohan Deb
Triple: [Hindu College, Calcutta, foundedBy, Gopi Mohan Deb]
Generated description
Gopi Mohan Deb was a prominent 19th-century Bengali zamindar and philanthropist known for his significant contributions to education and public institutions in colonial Calcutta.

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_69ee5bc496a88190af7deb7ab5e081de completed April 26, 2026, 6:39 p.m.
NER Named-entity recognition batch_69f60be63218819089ef0c5eb968db2f completed May 2, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25c0c271088190b5d77a3a72a7187a completed June 7, 2026, 7:04 p.m.
NEDg Description generation batch_6a25cbfacf408190b7064eca075f8f1b completed June 7, 2026, 7:52 p.m.
NED2 Entity disambiguation (via description) batch_6a25d10dc9f48190b0e8ed7743f20009 completed June 7, 2026, 8:14 p.m.
Created at: April 26, 2026, 8:21 p.m.