Triple
T15755569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KC2 |
E381958
|
entity |
| Predicate | aircraftFamily |
P1524
|
FINISHED |
| Object | Voyager |
E81561
|
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: Voyager | Statement: [KC2, aircraftFamily, Voyager]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Voyager Context triple: [KC2, aircraftFamily, Voyager]
-
A.
Voyager
chosen
Voyager is the Royal Air Force’s multi-role tanker transport aircraft, providing air-to-air refuelling and strategic airlift capabilities.
-
B.
Voyager
Voyager is a class of high-speed diesel-electric multiple unit trains used for intercity passenger services in the United Kingdom.
-
C.
Voyager
Voyager is South African Airways’ loyalty program that rewards frequent flyers with miles redeemable for flights, upgrades, and other travel benefits.
-
D.
Voyager
Voyager is a film adaptation of Max Frisch’s novel "Homo Faber," exploring themes of fate, identity, and the consequences of rationalism through the journey of an emotionally detached engineer.
-
E.
Voyager
Voyager is a science fiction novel by Diana Gabaldon, part of the Outlander series, that follows time-traveling nurse Claire Fraser as she reunites with her 18th-century husband Jamie after decades apart.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b1ff4881909d5240d1d30f5c8b |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff87714a8481909f8489c73ac89c11 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.