Triple
T3917032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LMS Princess Royal Class |
E88865
|
entity |
| Predicate | numberPreserved |
P17062
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [LMS Princess Royal Class, numberPreserved, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberPreserved Context triple: [LMS Princess Royal Class, numberPreserved, 2]
-
A.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
B.
preservationFactor
Indicates the degree to which something is protected, maintained, or kept intact over time, often moderating how much change, loss, or degradation occurs.
-
C.
preservedUnits
chosen
Indicates that certain units or components of something have been kept intact and unchanged rather than altered, removed, or destroyed.
-
D.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
E.
partiallyPreserved
Indicates that the referenced entity or object is only incompletely intact, with some parts missing, damaged, or lost while others remain.
- 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.