Triple
T3249794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Storm |
E68147
|
entity |
| Predicate | portraysMarriageAs |
P21095
|
FINISHED |
| Object | compatible with unspoken desires |
—
|
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: compatible with unspoken desires | Statement: [The Storm, portraysMarriageAs, compatible with unspoken desires]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysMarriageAs Context triple: [The Storm, portraysMarriageAs, compatible with unspoken desires]
-
A.
marriageCharacterization
chosen
Indicates how a marriage is described, evaluated, or characterized in terms of its qualities, dynamics, or nature.
-
B.
portraysRelationship
Indicates that one entity depicts, represents, or illustrates a relationship between other entities.
-
C.
marriageContext
Indicates the situational or cultural circumstances under which a marriage occurs or exists, such as legal, social, or religious conditions surrounding the marital relationship.
-
D.
marriageType
Indicates the specific legal or social category of a marriage relationship that exists between two spouses.
-
E.
marries
Indicates that one entity enters into a legally or socially recognized marital union with another 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.