Triple
T21014917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airwave |
E517647
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Airwave network |
E517647
|
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: Airwave network | Statement: [Airwave, fullName, Airwave network]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Airwave network Context triple: [Airwave, fullName, Airwave network]
-
A.
Airwave
chosen
Airwave is the secure digital radio communications network used by UK emergency services and public safety organizations for mission-critical voice and data.
-
B.
AVE network
The AVE network is Spain’s high-speed rail system that connects major cities across the country with fast, long-distance train services.
-
C.
AIRCOM
AIRCOM is NATO’s Allied Air Command headquartered at Ramstein Air Base, responsible for commanding and controlling the Alliance’s air and space operations in Europe.
-
D.
Skylink
Skylink is an automated people mover system that transports passengers between terminals at Dallas/Fort Worth International Airport.
-
E.
Aurora Network
Aurora Network is a European university alliance focused on collaboration in research, education, and innovation among its member institutions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5764188190829de6f5abd6e00f |
completed | April 21, 2026, 4:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a093b6369fc81909ff15a48a8a640e2 |
completed | May 17, 2026, 3:52 a.m. |
Created at: April 16, 2026, 1:54 p.m.