Triple

T24625610
Position Surface form Disambiguated ID Type / Status
Subject Magnolia Hotel Dallas E609531 entity
Predicate ownedBy P347 FINISHED
Object Stout Street Hospitality
Stout Street Hospitality is a hotel management and development company known for operating boutique and upscale properties across the United States.
 E1644287 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: Stout Street Hospitality | Statement: [Magnolia Hotel Dallas, ownedBy, Stout Street Hospitality]
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: Stout Street Hospitality
Triple: [Magnolia Hotel Dallas, ownedBy, Stout Street Hospitality]
Generated description
Stout Street Hospitality is a hotel management and development company known for operating boutique and upscale properties across the United States.

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_69e2c4d1d3708190a0f2dc6a3a8523bb completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2aab63f0c8190a459eec33af403de completed April 30, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1004855c188190817d2f4da6ca0372 completed May 22, 2026, 7:23 a.m.
NEDg Description generation batch_6a100628bf1c819082c4aae29969b5c6 completed May 22, 2026, 7:30 a.m.
NED2 Entity disambiguation (via description) batch_6a1006d990b48190952b59d5685ea626 completed May 22, 2026, 7:33 a.m.
Created at: April 18, 2026, 2:32 a.m.