Triple

T27460611
Position Surface form Disambiguated ID Type / Status
Subject Isla Verde district E692727 entity
Predicate hasHotel P4287 FINISHED
Object Fairmont El San Juan Hotel
Fairmont El San Juan Hotel is a historic luxury beachfront resort in Puerto Rico known for its vibrant nightlife, elegant design, and prominent location near San Juan.
E1773438 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: Fairmont El San Juan Hotel | Statement: [Isla Verde district, hasHotel, Fairmont El San Juan Hotel]
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: Fairmont El San Juan Hotel
Triple: [Isla Verde district, hasHotel, Fairmont El San Juan Hotel]
Generated description
Fairmont El San Juan Hotel is a historic luxury beachfront resort in Puerto Rico known for its vibrant nightlife, elegant design, and prominent location near San Juan.

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_69ef5207903881909427745cda05d27a completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62df94be88190bcb43f8106c762dd completed May 2, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b265070c81909a92a6d644bce0d0 completed May 24, 2026, 8:10 a.m.
NEDg Description generation batch_6a12b379225c8190aca2d280575a3f7a completed May 24, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_6a12b44191688190899b55266e559ede completed May 24, 2026, 8:18 a.m.
Created at: April 27, 2026, 12:50 p.m.