Triple

T24334050
Position Surface form Disambiguated ID Type / Status
Subject Prado Dam E613327 entity
Predicate nearFacility P2064 FINISHED
Object Prado Regional Park
Prado Regional Park is a large recreational area in Southern California offering camping, fishing, hiking, and various outdoor activities around a reservoir and natural open spaces.
E1629592 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: Prado Regional Park | Statement: [Prado Dam, nearFacility, Prado Regional Park]
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: Prado Regional Park
Triple: [Prado Dam, nearFacility, Prado Regional Park]
Generated description
Prado Regional Park is a large recreational area in Southern California offering camping, fishing, hiking, and various outdoor activities around a reservoir and natural open spaces.

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_69e2d7dcc5a08190b53691130d56cbc4 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292f381b08190b529a765a5d5e89b completed April 29, 2026, 11:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9ee128c81908fc342b68f334339 completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fceb8193c81908d490d950bcf783a completed May 22, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcf1f1d688190afb6492fdc1819d2 completed May 22, 2026, 3:35 a.m.
Created at: April 18, 2026, 1:56 a.m.