Triple

T36299403

Position	Surface form	Disambiguated ID	Type / Status
Subject	Deštné v Orlických horách	`E893464`	entity
Predicate	hasSkiResortName	`P35251`	FINISHED
Object	Ski centrum Deštné Ski centrum Deštné is a ski resort in the Orlické Mountains of the Czech Republic, offering downhill slopes, lifts, and winter sports facilities for visitors.	`E2178396`	NE FINISHED

How this triple was built (3 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: Ski centrum Deštné | Statement: [Deštné v Orlických horách, hasSkiResortName, Ski centrum Deštné]

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: Ski centrum Deštné
Triple: [Deštné v Orlických horách, hasSkiResortName, Ski centrum Deštné]

Generated description

Ski centrum Deštné is a ski resort in the Orlické Mountains of the Czech Republic, offering downhill slopes, lifts, and winter sports facilities for visitors.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: hasSkiResortName
Context triple: [Deštné v Orlických horách, hasSkiResortName, Ski centrum Deštné]

A. hasSkiResortType
Indicates that an entity is associated with, or classified by, a specific type or category of ski resort.
B. hasSkiResortFeature
Indicates that a ski resort possesses or offers a specific feature, amenity, or characteristic.
C. skiAreaName chosen
Indicates that an entity has a specific name used to identify a ski area.
D. hasSkiCenter
Indicates that a location or entity possesses or hosts a ski center as one of its facilities or features.
E. hasSkiResortNearby
Indicates that one location is situated close enough to another location that it can be considered to have a ski resort in its vicinity.
F. None of above.

Provenance (6 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_69f76e4a61f0819084a2b68dbbb4efc6`	completed	May 3, 2026, 3:48 p.m.
NER	Named-entity recognition	`batch_69f7ba6d06f48190a71b5a2f19e2232f`	completed	May 3, 2026, 9:13 p.m.
NED1	Entity disambiguation (via context triple)	`batch_6a397d802d948190b95f4d1aff327290`	completed	June 22, 2026, 6:22 p.m.
NEDg	Description generation	`batch_6a3982c390f081908fa6f1e205358ca1`	completed	June 22, 2026, 6:45 p.m.
NED2	Entity disambiguation (via description)	`batch_6a3983802c3c81908b0cd37ce3a04f53`	completed	June 22, 2026, 6:48 p.m.
PD	Predicate disambiguation	`batch_69f7b9a4aad48190a62e41c5e39339d9`	completed	May 3, 2026, 9:09 p.m.

Created at: May 3, 2026, 4:09 p.m.