Triple

T38022201
Position Surface form Disambiguated ID Type / Status
Subject Palm Beach Gardens E948668 entity
Predicate hasAttraction P105 FINISHED
Object Downtown at the Gardens
Downtown at the Gardens is an open-air shopping, dining, and entertainment complex serving as a popular lifestyle destination in Palm Beach Gardens, Florida.
E2253857 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: Downtown at the Gardens | Statement: [Palm Beach Gardens, hasAttraction, Downtown at the Gardens]
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: Downtown at the Gardens
Triple: [Palm Beach Gardens, hasAttraction, Downtown at the Gardens]
Generated description
Downtown at the Gardens is an open-air shopping, dining, and entertainment complex serving as a popular lifestyle destination in Palm Beach Gardens, Florida.

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_69f76efc10448190aff5fb566b98f952 completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbc9720cb081908f8a92db9e7e44f8 completed May 6, 2026, 11:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41543d43708190a6d6e8da5b6e41e2 completed June 28, 2026, 5:05 p.m.
NEDg Description generation batch_6a4157ffadbc819092aafa34626b3cd5 completed June 28, 2026, 5:21 p.m.
NED2 Entity disambiguation (via description) batch_6a415860f9e88190bb1c1fbbc2ef0e37 completed June 28, 2026, 5:22 p.m.
Created at: May 3, 2026, 4:20 p.m.