Triple

T33492403
Position Surface form Disambiguated ID Type / Status
Subject St. Georg E857772 entity
Predicate contains P35 FINISHED
Object St. Georg Hospital (Asklepios Klinik St. Georg)
St. Georg Hospital (Asklepios Klinik St. Georg) is a major Asklepios-operated acute care hospital in Hamburg, Germany, providing a wide range of specialized medical services.
E2054375 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: St. Georg Hospital (Asklepios Klinik St. Georg) | Statement: [St. Georg, contains, St. Georg Hospital (Asklepios Klinik St. Georg)]
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: St. Georg Hospital (Asklepios Klinik St. Georg)
Triple: [St. Georg, contains, St. Georg Hospital (Asklepios Klinik St. Georg)]
Generated description
St. Georg Hospital (Asklepios Klinik St. Georg) is a major Asklepios-operated acute care hospital in Hamburg, Germany, providing a wide range of specialized medical services.

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_69f3497547608190a1a0f2365fb713ee completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e567ed788190a135121a1c660ecc completed May 3, 2026, 6:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3595bd71b88190b2936f58cd0cab5e completed June 19, 2026, 7:17 p.m.
NEDg Description generation batch_6a359cf768688190b8a6c6e965bb7726 completed June 19, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_6a359d6c6c548190a45e99602faa7aba completed June 19, 2026, 7:50 p.m.
Created at: May 1, 2026, 1:38 a.m.