Triple

T27169158
Position Surface form Disambiguated ID Type / Status
Subject Agumbe E682856 entity
Predicate tourismAttraction P530 FINISHED
Object Koodlu Theertha Falls
Koodlu Theertha Falls is a scenic waterfall nestled in the lush Western Ghats near Agumbe in Karnataka, India, known for its serene forest setting and natural pool.
E1775454 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: Koodlu Theertha Falls | Statement: [Agumbe, tourismAttraction, Koodlu Theertha Falls]
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: Koodlu Theertha Falls
Triple: [Agumbe, tourismAttraction, Koodlu Theertha Falls]
Generated description
Koodlu Theertha Falls is a scenic waterfall nestled in the lush Western Ghats near Agumbe in Karnataka, India, known for its serene forest setting and natural pool.

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_69eefacf6e788190a75a64399d9e3109 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f62545e210819090004d7c65f4898d completed May 2, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbbf95e8819098917fcf1eb163ea completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bce144b481909ef46950ddf8236a completed May 24, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_6a12bd75c610819081ae1b4f7fedb4cb completed May 24, 2026, 8:57 a.m.
Created at: April 27, 2026, 9:22 a.m.