Triple

T26958317
Position Surface form Disambiguated ID Type / Status
Subject Bedford Springs Hotel E678967 entity
Predicate brandName P1500 FINISHED
Object Omni Bedford Springs Resort
Omni Bedford Springs Resort is a historic luxury resort in Bedford, Pennsylvania, renowned for its mineral springs, grand architecture, and upscale spa and golf amenities.
E1751725 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: Omni Bedford Springs Resort | Statement: [Bedford Springs Hotel, brandName, Omni Bedford Springs Resort]
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: Omni Bedford Springs Resort
Triple: [Bedford Springs Hotel, brandName, Omni Bedford Springs Resort]
Generated description
Omni Bedford Springs Resort is a historic luxury resort in Bedford, Pennsylvania, renowned for its mineral springs, grand architecture, and upscale spa and golf amenities.

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_69eeeb4e75f08190b14fc91ca4a91488 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f620ea07088190b8e949161d6113fa completed May 2, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12299d1d5c8190bb09961ff214efd7 completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122a5774408190b156c205e764e896 completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122b1ce9a48190935b3499f77d0a1e completed May 23, 2026, 10:33 p.m.
Created at: April 27, 2026, 6:29 a.m.