Triple
T1686893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassandra Wilder |
E36461
|
entity |
| Predicate | hasFictionalUniverseGenre |
P31344
|
FINISHED |
| Object | soap opera |
—
|
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: soap opera | Statement: [Cassandra Wilder, hasFictionalUniverseGenre, soap opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalUniverseGenre Context triple: [Cassandra Wilder, hasFictionalUniverseGenre, soap opera]
-
A.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
B.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
-
D.
hasMediaFranchise
Indicates that one entity is part of, or belongs to, a larger media franchise represented by another entity.
-
E.
hasFictionalLocation
Indicates that an entity is associated with, set in, or takes place within a location that exists only in fiction rather than in the real world.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aaf3359ce48190803b322db8ad6027 |
completed | March 6, 2026, 3:31 p.m. |
| PD | Predicate disambiguation | batch_69aa61b71cec8190b273588051058ebd |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69aaf33347e48190a32b6d0099e3d389 |
completed | March 6, 2026, 3:30 p.m. |
Created at: March 4, 2026, 7:29 p.m.