Triple

T30936568
Position Surface form Disambiguated ID Type / Status
Subject Dhenkanal district E788138 entity
Predicate hasNotablePlace P10233 FINISHED
Object Kapilash Wildlife Sanctuary
Kapilash Wildlife Sanctuary is a protected forest area in Odisha, India, known for its rich biodiversity, hilly terrain, and populations of elephants and other wildlife.
E1992894 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: Kapilash Wildlife Sanctuary | Statement: [Dhenkanal district, hasNotablePlace, Kapilash Wildlife Sanctuary]
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: Kapilash Wildlife Sanctuary
Triple: [Dhenkanal district, hasNotablePlace, Kapilash Wildlife Sanctuary]
Generated description
Kapilash Wildlife Sanctuary is a protected forest area in Odisha, India, known for its rich biodiversity, hilly terrain, and populations of elephants and other wildlife.

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_69f224c0b7fc819090cb89df60d23653 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692e5069c81908013503ba8d065d7 completed May 3, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f00ff5044819080239a9e4e79908c completed June 14, 2026, 7:29 p.m.
NEDg Description generation batch_6a2f0210c6dc8190953859020baa3729 completed June 14, 2026, 7:33 p.m.
NED2 Entity disambiguation (via description) batch_6a2f02d3ff748190adb82f02b7629721 completed June 14, 2026, 7:36 p.m.
Created at: April 29, 2026, 8:52 p.m.