Triple

T24357024
Position Surface form Disambiguated ID Type / Status
Subject Nojoqui Falls Park E613951 entity
Predicate hasAttraction P105 FINISHED
Object Nojoqui Falls
Nojoqui Falls is a picturesque seasonal waterfall in Santa Barbara County, California, known for its tall, thin cascade reached by a short forested hiking trail.
E1699213 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: Nojoqui Falls | Statement: [Nojoqui Falls Park, hasAttraction, Nojoqui 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: Nojoqui Falls
Triple: [Nojoqui Falls Park, hasAttraction, Nojoqui Falls]
Generated description
Nojoqui Falls is a picturesque seasonal waterfall in Santa Barbara County, California, known for its tall, thin cascade reached by a short forested hiking trail.

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_69e2d7dfe7f08190b7a1f3a36483ab05 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f29349ee188190a9d54b2c725b8a27 completed April 29, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9d2fb788190a407837d8599c847 completed May 22, 2026, 10:33 p.m.
NEDg Description generation batch_6a10e090e3408190aa8881f96d7e0a47 completed May 22, 2026, 11:02 p.m.
NED2 Entity disambiguation (via description) batch_6a10e0ed4c1881909fad8a7fcb0f3333 completed May 22, 2026, 11:04 p.m.
Created at: April 18, 2026, 2 a.m.