Triple
T5398408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Hopkins as Stevens |
E120713
|
entity |
| Predicate | emotionalCharacteristic |
P37384
|
FINISHED |
| Object | emotionally repressed |
—
|
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: emotionally repressed | Statement: [Anthony Hopkins as Stevens, emotionalCharacteristic, emotionally repressed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: emotionalCharacteristic Context triple: [Anthony Hopkins as Stevens, emotionalCharacteristic, emotionally repressed]
-
A.
emotionalDynamic
Indicates how emotions, moods, or affective states change, interact, or influence each other between entities over time.
-
B.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
C.
featuresMood
Indicates that something includes, presents, or conveys a particular mood or emotional atmosphere.
-
D.
associatedCharacterTrait
chosen
Indicates a relationship where a character is linked to, or described by, a particular trait or quality.
-
E.
feltIn
Indicates that a sensation, emotion, or effect is experienced within a particular location, context, or 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.