Triple
T31031670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oceania series |
E790743
|
entity |
| Predicate | worldbuildingFocus |
P193722
|
FINISHED |
| Object | maritime environments |
—
|
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: maritime environments | Statement: [Oceania series, worldbuildingFocus, maritime environments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldbuildingFocus Context triple: [Oceania series, worldbuildingFocus, maritime environments]
-
A.
worldbuildingFunction
Indicates the role or purpose something serves in constructing, shaping, or enriching an imagined world or setting.
-
B.
worldType
Indicates the classification or category of world or environment that an entity is associated with.
-
C.
worldName
Indicates that an entity has or is associated with a specific world’s name.
-
D.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
E.
fictionalUniverseLocation
Indicates that one entity is a location or setting within the fictional universe to which the other entity belongs or in which it takes place.
- 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_69f224c97a788190b5da1ead6038a74e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fd509cdc5c8190a5f2c451bc0d0b25 |
completed | May 8, 2026, 2:55 a.m. |
Created at: April 29, 2026, 8:59 p.m.