Triple
T6288954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassandra Cillian |
E140966
|
entity |
| Predicate | hasEmotionalArc |
P20798
|
FINISHED |
| Object | coping with terminal illness |
—
|
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: coping with terminal illness | Statement: [Cassandra Cillian, hasEmotionalArc, coping with terminal illness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmotionalArc Context triple: [Cassandra Cillian, hasEmotionalArc, coping with terminal illness]
-
A.
characterArc
chosen
Indicates the developmental journey or transformation a character undergoes over the course of a narrative.
-
B.
characterArcElement
Indicates that one element is a component or stage within a character’s overall developmental arc or transformation.
-
C.
hasMoralArc
Indicates that something follows a discernible trajectory of moral development, progress, or decline over time.
-
D.
hasProtagonistJourneyType
Indicates that a narrative work features a main character whose overarching journey follows a specific type or pattern (e.g., hero’s journey, coming-of-age, tragedy).
-
E.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0641a6ecc8190a63be0e3f0344a3f |
completed | March 22, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69c060df0d8881908215575862ef6831 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:26 p.m.