Triple
T16835245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 9M-MRD |
E409256
|
entity |
| Predicate | aircraftSerialNumber |
P125032
|
FINISHED |
| Object | Boeing 777-200ER airframe used as 9M-MRD |
—
|
LITERAL 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: Boeing 777-200ER airframe used as 9M-MRD | Statement: [9M-MRD, aircraftSerialNumber, Boeing 777-200ER airframe used as 9M-MRD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftSerialNumber Context triple: [9M-MRD, aircraftSerialNumber, Boeing 777-200ER airframe used as 9M-MRD]
-
A.
aircraftRegistration
Indicates that an aircraft is assigned a specific official registration identifier or code.
-
B.
wingNumber
Indicates the specific identifier or count assigned to a wing associated with an entity.
-
C.
spacecraftSerialNumber
Indicates the unique identifying serial number assigned to a specific spacecraft.
-
D.
aircraftRecord
Indicates a relationship where a record or entry documents information about an aircraft and its associated details.
-
E.
aircraftRegistrationInvolved
Indicates that a specific aircraft registration is involved in, associated with, or affected by a particular event, action, or record.
- F. None of above. chosen
Provenance (4 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_69d883952b048190887740a980b712ed |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b31aa44c8190b4f402f1898e6998 |
completed | April 18, 2026, 4:36 p.m. |
| PD | Predicate disambiguation | batch_69e32b87b4248190aaddb05e88452356 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:23 a.m.