Triple

T23686764
Position Surface form Disambiguated ID Type / Status
Subject Leeuwarden Air Base E585188 entity
Predicate hostsEvent P613 FINISHED
Object Frisian Flag exercise
Frisian Flag exercise is a large-scale multinational air combat training exercise held annually in the Netherlands, focusing on advanced tactical flying and interoperability among NATO and partner air forces.
E1594443 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: Frisian Flag exercise | Statement: [Leeuwarden Air Base, hostsEvent, Frisian Flag exercise]
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: Frisian Flag exercise
Triple: [Leeuwarden Air Base, hostsEvent, Frisian Flag exercise]
Generated description
Frisian Flag exercise is a large-scale multinational air combat training exercise held annually in the Netherlands, focusing on advanced tactical flying and interoperability among NATO and partner air forces.

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_69e249037ce0819088b149608e98f685 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1b5bf1c10819085d48c4225cc63fc completed April 29, 2026, 7:39 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f45c3407881909db4fcae7fcb8597 completed May 21, 2026, 5:49 p.m.
NEDg Description generation batch_6a0f4671511081908f0136d26bce0eb9 completed May 21, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_6a0f474266a08190b62dd3968b832a5a completed May 21, 2026, 5:56 p.m.
Created at: April 17, 2026, 6:52 p.m.