Triple
T11554154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ships of the line of the Royal Navy |
E273969
|
entity |
| Predicate | hasTypicalGunCountRange |
P43153
|
FINISHED |
| Object | 50 to over 100 guns |
—
|
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: 50 to over 100 guns | Statement: [Ships of the line of the Royal Navy, hasTypicalGunCountRange, 50 to over 100 guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalGunCountRange Context triple: [Ships of the line of the Royal Navy, hasTypicalGunCountRange, 50 to over 100 guns]
-
A.
numberOfGuns
chosen
Indicates the quantity of guns associated with a given entity or situation.
-
B.
hasSmallCalibreGuns
Indicates that the subject is equipped with or possesses guns of relatively small calibre compared to standard or typical armaments.
-
C.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
-
D.
ammunitionCapacity
Indicates the maximum amount of ammunition that something (typically a weapon or container) is designed to hold at one time.
-
E.
rangeStandardAmmunition
Indicates that the relationship specifies the standard type of ammunition used for a given range or weapon system.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a85b9ac8190a57c1fdaeacbe3d6 |
completed | April 10, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_69d85dc3fc2c8190bed7e2111301a77c |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:37 p.m.