Triple

T26996003
Position Surface form Disambiguated ID Type / Status
Subject Forest Department of Kerala E679981 entity
Predicate oversees P46 FINISHED
Object Shendurney Wildlife Sanctuary
Shendurney Wildlife Sanctuary is a protected forest and wildlife reserve in Kerala, India, known for its rich biodiversity, evergreen forests, and scenic reservoir landscapes.
E1786621 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: Shendurney Wildlife Sanctuary | Statement: [Forest Department of Kerala, oversees, Shendurney 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: Shendurney Wildlife Sanctuary
Triple: [Forest Department of Kerala, oversees, Shendurney Wildlife Sanctuary]
Generated description
Shendurney Wildlife Sanctuary is a protected forest and wildlife reserve in Kerala, India, known for its rich biodiversity, evergreen forests, and scenic reservoir landscapes.

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_69eeeb52908c8190bd246244686aa455 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f6219447488190a7eac0d954c85555 completed May 2, 2026, 4:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12e42f749c8190828b02fa6eba7229 completed May 24, 2026, 11:42 a.m.
NEDg Description generation batch_6a12e4da65dc8190801cafed5fb95685 completed May 24, 2026, 11:45 a.m.
NED2 Entity disambiguation (via description) batch_6a12e5a642e4819095c21cfe6a85f12f completed May 24, 2026, 11:48 a.m.
Created at: April 27, 2026, 6:54 a.m.