Triple

T24210984
Position Surface form Disambiguated ID Type / Status
Subject Stuart Collection at UC San Diego E600541 entity
Predicate hasPart P35 FINISHED
Object La Jolla Vista View
La Jolla Vista View is a large-scale outdoor artwork by sculptor William Wegman, installed on the UC San Diego campus as part of the Stuart Collection.
E1623680 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: La Jolla Vista View | Statement: [Stuart Collection at UC San Diego, hasPart, La Jolla Vista View]
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: La Jolla Vista View
Triple: [Stuart Collection at UC San Diego, hasPart, La Jolla Vista View]
Generated description
La Jolla Vista View is a large-scale outdoor artwork by sculptor William Wegman, installed on the UC San Diego campus as part of the Stuart Collection.

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_69e2953344c48190875730c7d52112a0 completed April 17, 2026, 8:16 p.m.
NER Named-entity recognition batch_69f28202f56c81909bd6a624d33d452e completed April 29, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbd1de230819097f6d540b46efc75 completed May 22, 2026, 2:19 a.m.
NEDg Description generation batch_6a0fbe09c6e4819093b71509780fcec0 completed May 22, 2026, 2:23 a.m.
NED2 Entity disambiguation (via description) batch_6a0fbed0cbc48190963e3764a8481cbf completed May 22, 2026, 2:26 a.m.
Created at: April 17, 2026, 11:55 p.m.