Triple
T15081356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HMS Excellent (1787) |
E360150
|
entity |
| Predicate | gunneryReputation |
P24407
|
FINISHED |
| Object | highly accurate gunnery |
—
|
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: highly accurate gunnery | Statement: [HMS Excellent (1787), gunneryReputation, highly accurate gunnery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gunneryReputation Context triple: [HMS Excellent (1787), gunneryReputation, highly accurate gunnery]
-
A.
tacticalReputation
Indicates the perceived level of skill, reliability, or effectiveness an entity has in planning and executing tactics within a given context.
-
B.
militaryReputation
chosen
Indicates the perceived standing or esteem of an entity based on its past or present military performance, conduct, or capabilities.
-
C.
navalRating
Indicates the assessed level of naval strength, capability, or performance attributed to an entity.
-
D.
haveReputation
Indicates that an entity is recognized or regarded in a certain way by others, reflecting its perceived character, quality, or status.
-
E.
seaReputation
Indicates the perceived status, trustworthiness, or renown of an entity specifically within maritime or sea-related contexts.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69dff80008c88190840f94222f867478 |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:03 a.m.