Triple

T30536174
Position Surface form Disambiguated ID Type / Status
Subject Garnet Health Medical Center E777151 entity
Predicate formerlyKnownAs P65 FINISHED
Object Orange Regional Medical Center
Orange Regional Medical Center was the former name of Garnet Health Medical Center, a major hospital serving the Hudson Valley region of New York.
E1919349 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: Orange Regional Medical Center | Statement: [Garnet Health Medical Center, formerlyKnownAs, Orange Regional Medical Center]
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: Orange Regional Medical Center
Triple: [Garnet Health Medical Center, formerlyKnownAs, Orange Regional Medical Center]
Generated description
Orange Regional Medical Center was the former name of Garnet Health Medical Center, a major hospital serving the Hudson Valley region of New York.

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_69f2249d183c8190b79937c1768d2163 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68850f3088190b84f1b63101d47e9 completed May 2, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be81f03c8190874293df30769b4e completed June 9, 2026, 7:19 a.m.
NEDg Description generation batch_6a27c0a62c508190b40eca87b6bef1a2 completed June 9, 2026, 7:28 a.m.
NED2 Entity disambiguation (via description) batch_6a27c10324348190a44216514590a529 completed June 9, 2026, 7:30 a.m.
Created at: April 29, 2026, 8:18 p.m.