Triple

T30095259
Position Surface form Disambiguated ID Type / Status
Subject Faena Group E764846 entity
Predicate developedProject P80445 FINISHED
Object Faena House
Faena House is a luxury oceanfront residential building in Miami Beach known for its high-end design, expansive terraces, and association with the upscale Faena District.
E1899531 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: Faena House | Statement: [Faena Group, developedProject, Faena House]
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: Faena House
Triple: [Faena Group, developedProject, Faena House]
Generated description
Faena House is a luxury oceanfront residential building in Miami Beach known for its high-end design, expansive terraces, and association with the upscale Faena District.

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_69f22474e4288190b5f895fe3974aa92 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67d8f52e88190b3a11f62835ea328 completed May 2, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27432af84881909f6dfa4acb62e18d completed June 8, 2026, 10:33 p.m.
NEDg Description generation batch_6a2743cf9c208190965b51fdc3713824 completed June 8, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_6a27448fcf748190a4e15ef2f89f56f5 completed June 8, 2026, 10:39 p.m.
Created at: April 29, 2026, 7:07 p.m.