Triple

T32519529
Position Surface form Disambiguated ID Type / Status
Subject RIPE Meeting E831143 entity
Predicate takesPlaceIn P373 FINISHED
Object RIPE region
The RIPE region is the geographical area covered by the Réseaux IP Européens Network Coordination Centre, encompassing Europe, the Middle East, and parts of Central Asia for Internet resource management and coordination.
 E37217 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: RIPE region | Statement: [RIPE Meeting, takesPlaceIn, RIPE region]
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: RIPE region
Triple: [RIPE Meeting, takesPlaceIn, RIPE region]
Generated description
The RIPE region is the geographical area covered by the Réseaux IP Européens Network Coordination Centre, encompassing Europe, the Middle East, and parts of Central Asia for Internet resource management and coordination.

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_69f34923e1548190be0524205d8cdf8f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c4b63b088190b343410304ad151f completed May 3, 2026, 3:44 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34706904708190a7e3c94eef3cebe5 completed June 18, 2026, 10:25 p.m.
NEDg Description generation batch_6a34716ee2c881909718e2f8ff55dd91 completed June 18, 2026, 10:30 p.m.
NED2 Entity disambiguation (via description) batch_6a3472e5099481908eb453aba2047e18 completed June 18, 2026, 10:36 p.m.
Created at: May 1, 2026, 1 a.m.