Triple
T13728041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Black Prince (1861) |
E329716
|
entity |
| Predicate | armourCoverage |
P111322
|
FINISHED |
| Object | central portion of hull along waterline |
—
|
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: central portion of hull along waterline | Statement: [HMS Black Prince (1861), armourCoverage, central portion of hull along waterline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armourCoverage Context triple: [HMS Black Prince (1861), armourCoverage, central portion of hull along waterline]
-
A.
armourProtection
Indicates that one entity provides protective armor or defensive covering for another entity.
-
B.
armour
Indicates that an entity provides protective covering or defense for another entity.
-
C.
armourThickness
Indicates the measured thickness of an entity’s protective armor in the context of defense or shielding.
-
D.
armorType
Indicates the specific category or classification of protective armor associated with an entity.
-
E.
armourThicknessMin
Indicates the minimum measured or specified thickness of an object's armor in the described context.
- 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_69d80772315881908f980cae40d91664 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f746cc8190abde237bbb7e6c78 |
completed | April 14, 2026, 8:59 a.m. |
| PD | Predicate disambiguation | batch_69dbbe92d77c81908e0244cffb7f78c5 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:55 p.m.