Triple
T2200858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aileen Wuornos in Monster |
E50483
|
entity |
| Predicate | primaryMotivationInFiction |
P19457
|
FINISHED |
| Object | survival |
—
|
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: survival | Statement: [Aileen Wuornos in Monster, primaryMotivationInFiction, survival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryMotivationInFiction Context triple: [Aileen Wuornos in Monster, primaryMotivationInFiction, survival]
-
A.
literaryPurpose
Indicates the intended function, effect, or communicative goal that a text or passage is meant to achieve within a literary context.
-
B.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
-
C.
motivationFor
chosen
Indicates that one entity serves as the reason, drive, or incentive behind another entity’s action, state, or occurrence.
-
D.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
E.
fictionalMedium
Indicates that a work of fiction is presented or conveyed through a particular medium or format (such as a book, film, game, or comic).
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbfa06bb4819092d7021358846e5f |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.