Triple

T29458019

Position	Surface form	Disambiguated ID	Type / Status
Subject	Leblon Beach	`E747151`	entity
Predicate	hasViewOf	`P854`	FINISHED
Object	Two Brothers Mountain Two Brothers Mountain is a distinctive twin-peaked granite formation in Rio de Janeiro, Brazil, that serves as an iconic backdrop to the city’s southern beaches.	`E2284399`	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: Two Brothers Mountain | Statement: [Leblon Beach, hasViewOf, Two Brothers Mountain]

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: Two Brothers Mountain
Triple: [Leblon Beach, hasViewOf, Two Brothers Mountain]

Generated description

Two Brothers Mountain is a distinctive twin-peaked granite formation in Rio de Janeiro, Brazil, that serves as an iconic backdrop to the city’s southern beaches.

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_69f0bd4125f88190b56104591351619c`	completed	April 28, 2026, 1:59 p.m.
NER	Named-entity recognition	`batch_69f66b6e727c81909d590686a0096fcd`	completed	May 2, 2026, 9:23 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a438a27783481908df1696aa7f7af5d`	completed	June 30, 2026, 9:19 a.m.
NEDg	Description generation	`batch_6a438b5d9c608190a33ffed9b9ff805e`	completed	June 30, 2026, 9:24 a.m.
NED2	Entity disambiguation (via description)	`batch_6a438bd204e08190a4ed75eecc35868f`	completed	June 30, 2026, 9:26 a.m.

Created at: April 28, 2026, 3:47 p.m.