Triple
T20490400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Devonshire-class armoured cruiser |
E502727
|
entity |
| Predicate | hasArmourCharacteristic |
P140280
|
FINISHED |
| Object | heavy armour for its time |
—
|
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: heavy armour for its time | Statement: [Devonshire-class armoured cruiser, hasArmourCharacteristic, heavy armour for its time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArmourCharacteristic Context triple: [Devonshire-class armoured cruiser, hasArmourCharacteristic, heavy armour for its time]
-
A.
hasTypicalArmor
Indicates that an entity normally wears or is equipped with a standard or characteristic type of armor.
-
B.
wearsArmor
Indicates that an entity is equipped with or dressed in armor as protective gear.
-
C.
armourCoverage
Indicates the extent or area of a subject’s body or structure that is protected or covered by armour.
-
D.
armourProtection
Indicates that one entity provides protective armor or defensive covering for another entity.
-
E.
armour
Indicates that an entity provides protective covering or defense for another entity.
- 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_69e0b4b0373881909dd3e9387f82eab4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cb8e7848190a1dc497a10ae798c |
completed | April 20, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69e59fcdf6e08190a604204615dc56e6 |
completed | April 20, 2026, 3:38 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:35 a.m.