Triple

T27302702

Position	Surface form	Disambiguated ID	Type / Status
Subject	Robert von Hagge	`E688958`	entity
Predicate	designed	`P184`	FINISHED
Object	Doral Blue Monster redesign The Doral Blue Monster redesign is a modern reimagining of the famed Miami golf course, updating its strategic layout and challenge while preserving its championship character.	`E1767292`	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: Doral Blue Monster redesign | Statement: [Robert von Hagge, designed, Doral Blue Monster redesign]

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: Doral Blue Monster redesign
Triple: [Robert von Hagge, designed, Doral Blue Monster redesign]

Generated description

The Doral Blue Monster redesign is a modern reimagining of the famed Miami golf course, updating its strategic layout and challenge while preserving its championship character.

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_69ef355b931c8190a63cafaf7bcc008b`	completed	April 27, 2026, 10:07 a.m.
NER	Named-entity recognition	`batch_69f627856b288190929d4c5bff6a91d4`	completed	May 2, 2026, 4:34 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a129cace7d8819089ab0ec258a0e176`	completed	May 24, 2026, 6:37 a.m.
NEDg	Description generation	`batch_6a129dc563e081909b6e07e29aad6ddb`	completed	May 24, 2026, 6:42 a.m.
NED2	Entity disambiguation (via description)	`batch_6a129e62fd248190b264904e77be6e5e`	completed	May 24, 2026, 6:44 a.m.

Created at: April 27, 2026, 11:23 a.m.