Triple
T35081638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamia (Drag Me to Hell) |
E1012451
|
entity |
| Predicate | perceptionByCharacters |
P93383
|
FINISHED |
| Object | unstoppable force |
—
|
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: unstoppable force | Statement: [Lamia (Drag Me to Hell), perceptionByCharacters, unstoppable force]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceptionByCharacters Context triple: [Lamia (Drag Me to Hell), perceptionByCharacters, unstoppable force]
-
A.
perceivedCharacter
Indicates how one entity subjectively views or interprets the traits, qualities, or persona of another entity.
-
B.
perceptionByHumans
Indicates that something is perceived, sensed, or experienced through human sensory or cognitive processes.
-
C.
perceivedAsByCharacters
chosen
Indicates how something is viewed, interpreted, or understood by one or more characters.
-
D.
analyzedByCharacter
Indicates that something (such as an event, object, or situation) is examined, interpreted, or evaluated by a particular character.
-
E.
characterResolution
Indicates the process or outcome by which a character’s conflicts, arcs, or internal struggles are brought to a conclusion or clarified within a narrative.
- 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_69f76dd32c008190853aef6028f60208 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:01 p.m.