Triple
T15565497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vessels in a Moderate Breeze |
E371103
|
entity |
| Predicate | portraysSeaState |
P13023
|
FINISHED |
| Object | moderately rough sea |
—
|
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: moderately rough sea | Statement: [Vessels in a Moderate Breeze, portraysSeaState, moderately rough sea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysSeaState Context triple: [Vessels in a Moderate Breeze, portraysSeaState, moderately rough sea]
-
A.
oceanState
Indicates the condition or status of an ocean (such as calmness, turbulence, or other physical characteristics) at a given time or location.
-
B.
hasSeaCondition
chosen
Indicates that an entity is associated with or characterized by a particular state or condition of the sea.
-
C.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
-
D.
seaOf
Indicates a relationship where one entity is metaphorically or literally surrounded or filled by another like a vast sea, emphasizing overwhelming abundance or expansiveness.
-
E.
stateOfHarbor
Indicates the current operational or physical condition or status of a harbor.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ddd753c8190b51eaef433258081 |
completed | April 16, 2026, 2:47 a.m. |
| PD | Predicate disambiguation | batch_69deda7e6e748190b29ccce23298afef |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:10 a.m.