Triple
T34173983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napier Lion engine family |
E876616
|
entity |
| Predicate | bankArrangement |
P178479
|
FINISHED |
| Object | three banks of four cylinders |
—
|
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: three banks of four cylinders | Statement: [Napier Lion engine family, bankArrangement, three banks of four cylinders]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bankArrangement Context triple: [Napier Lion engine family, bankArrangement, three banks of four cylinders]
-
A.
bankSection
Indicates a specific part or division within a bank that is associated with or relevant to the related entity.
-
B.
banksHost
Indicates that a financial institution (bank) provides hosting or custodial services for another entity’s assets, accounts, or operations.
-
C.
linkedByCurrencyArrangementWith
Indicates that two entities are connected through a formal currency-related arrangement, such as a peg, union, swap line, or other structured monetary linkage.
-
D.
banksOften
Indicates that the subject frequently or habitually engages in banking activities with the object (such as depositing, withdrawing, or otherwise using banking services).
-
E.
bankingType
Indicates the category or model of banking relationship or services associated with an entity (e.g., retail, corporate, investment).
- 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f710aaff588190adc6cc5b7d5424cc |
completed | May 3, 2026, 9:08 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
| PDg | Predicate description generation | batch_69f70fddd43c819088dee5a448c72cbe |
completed | May 3, 2026, 9:05 a.m. |
Created at: May 1, 2026, 1:54 a.m.