Triple

T24547102
Position Surface form Disambiguated ID Type / Status
Subject European VLBI Network E607255 entity
Predicate hasMember P10 FINISHED
Object Medicina Radio Observatory
The Medicina Radio Observatory is an Italian radio astronomy facility near Bologna that operates large radio telescopes used for interferometric observations and participation in international networks.
 E1638275 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: Medicina Radio Observatory | Statement: [European VLBI Network, hasMember, Medicina Radio Observatory]
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: Medicina Radio Observatory
Triple: [European VLBI Network, hasMember, Medicina Radio Observatory]
Generated description
The Medicina Radio Observatory is an Italian radio astronomy facility near Bologna that operates large radio telescopes used for interferometric observations and participation in international networks.

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_69e2c4c9bf94819082d05da6f5c29907 completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a8caba8c819082c3bf33b6ff9cd0 completed April 30, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0feea9d09c8190bbf86d7a4bab70ad completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0fef20efe08190bb4cb412e2473ae5 completed May 22, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff097dd8881908bb83d84a6581ef7 completed May 22, 2026, 5:58 a.m.
Created at: April 18, 2026, 2:27 a.m.