Triple
T33458822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seduction by Mrs. Robinson |
E856850
|
entity |
| Predicate | influencedTrope |
P9
|
FINISHED |
| Object | older woman seducing younger man in film and television |
—
|
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: older woman seducing younger man in film and television | Statement: [Seduction by Mrs. Robinson, influencedTrope, older woman seducing younger man in film and television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencedTrope Context triple: [Seduction by Mrs. Robinson, influencedTrope, older woman seducing younger man in film and television]
-
A.
influenceOf
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
B.
influenced
chosen
Indicates that one entity has affected, shaped, or altered another entity’s state, behavior, or characteristics.
-
C.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
-
D.
influencedAspectOf
Indicates that one entity has affected, shaped, or altered a particular aspect or component of another entity.
-
E.
influencesInStory
Indicates that one entity affects, shapes, or alters another entity within the context of a narrative or story.
- 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_69f3497281a08190b4705de0b5f26ba7 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: May 1, 2026, 1:37 a.m.