Triple
T9656711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Princess of Thule |
E233470
|
entity |
| Predicate | hasFictionalGenreElement |
P69830
|
FINISHED |
| Object | romance |
—
|
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: romance | Statement: [A Princess of Thule, hasFictionalGenreElement, romance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalGenreElement Context triple: [A Princess of Thule, hasFictionalGenreElement, romance]
-
A.
hasFictionalUniverseGenre
Indicates that a fictional universe is associated with a particular genre that characterizes its overall style, themes, or narrative type.
-
B.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
C.
hasFictionalProductionType
chosen
Indicates that an entity is associated with a specific type or category of fictional production (such as a genre, format, or style).
-
D.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
E.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
- 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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bdd5c0c8190a6c82a1609454d1b |
completed | April 1, 2026, 10:27 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b3239c8190b3ae3b9bd121e4bd |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:14 p.m.