Triple

T35182879
Position Surface form Disambiguated ID Type / Status
Subject Exercise Pitch Black E1015900 entity
Predicate usesAirspace P22328 FINISHED
Object Bradshaw Field Training Area
Bradshaw Field Training Area is a large Australian Defence Force military training range in the Northern Territory used for major air and ground exercises.
E2129406 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: Bradshaw Field Training Area | Statement: [Exercise Pitch Black, usesAirspace, Bradshaw Field Training Area]
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: Bradshaw Field Training Area
Triple: [Exercise Pitch Black, usesAirspace, Bradshaw Field Training Area]
Generated description
Bradshaw Field Training Area is a large Australian Defence Force military training range in the Northern Territory used for major air and ground exercises.

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_69f76ddd815c8190b822eea06630f9fb completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7a07937988190841ae789d824406d completed May 3, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37fb1ca8748190b4509cc1825899a2 completed June 21, 2026, 2:54 p.m.
NEDg Description generation batch_6a37fbbc2de88190b6c0cb4163bf290f completed June 21, 2026, 2:57 p.m.
NED2 Entity disambiguation (via description) batch_6a37fcfc8c308190928623978df0d45a completed June 21, 2026, 3:02 p.m.
Created at: May 3, 2026, 4:02 p.m.