Triple

T30738937
Position Surface form Disambiguated ID Type / Status
Subject Government Vellore Medical College E782639 entity
Predicate regionServed P82 FINISHED
Object Vellore district
Vellore district is an administrative region in the Indian state of Tamil Nadu, known for its historic Vellore Fort, educational and medical institutions, and a mix of urban and rural settlements.
E1759955 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: Vellore district | Statement: [Government Vellore Medical College, regionServed, Vellore district]
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: Vellore district
Triple: [Government Vellore Medical College, regionServed, Vellore district]
Generated description
Vellore district is an administrative region in the Indian state of Tamil Nadu, known for its historic Vellore Fort, educational and medical institutions, and a mix of urban and rural settlements.

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_69f224aeb1588190897d395e8ed2acb8 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68ee9435081908efcb423c2eaf1ab completed May 2, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a352f9515b88190af5307bf01f999fa completed June 19, 2026, 12:01 p.m.
NEDg Description generation batch_6a3530781f548190b29ceca0c6dcf672 completed June 19, 2026, 12:05 p.m.
NED2 Entity disambiguation (via description) batch_6a35325acae0819090ed2b885836836d completed June 19, 2026, 12:13 p.m.
Created at: April 29, 2026, 8:37 p.m.