Triple
T9603820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin-Baker MB 3 |
E231918
|
entity |
| Predicate | firstPrototypeSerialNumber |
P17884
|
FINISHED |
| Object | R2492 |
—
|
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: R2492 | Statement: [Martin-Baker MB 3, firstPrototypeSerialNumber, R2492]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstPrototypeSerialNumber Context triple: [Martin-Baker MB 3, firstPrototypeSerialNumber, R2492]
-
A.
firstChassisNumber
Indicates that the associated value is the earliest or initial chassis identification number assigned to a vehicle or mechanical unit.
-
B.
firstSerialisedIn
Indicates the original publication or medium in which something (such as a work or story) was first released in serialized form.
-
C.
firstSerializationYear
Indicates the year in which an entity (such as a work or series) was first serialized or began its initial serialized publication.
-
D.
serialNumber
chosen
Indicates a unique identifying code assigned to an individual item or instance within a series or batch.
-
E.
firstSeriesCode
Indicates that an entity is identified as the initial or primary series within a sequence, referenced by a specific code.
- F. None of above.
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_69ca8484838c8190b2049199d22fef70 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9a5cddf481909aa6b589bcb3e71a |
completed | April 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69ccd5a6fd2481908efd131e207b8143 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:08 p.m.