Triple
T33458820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seduction by Mrs. Robinson |
E856850
|
entity |
| Predicate | associatedCharacterAgeDifference |
P164683
|
FINISHED |
| Object | older woman and younger man |
—
|
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 and younger man | Statement: [Seduction by Mrs. Robinson, associatedCharacterAgeDifference, older woman and younger man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCharacterAgeDifference Context triple: [Seduction by Mrs. Robinson, associatedCharacterAgeDifference, older woman and younger man]
-
A.
protagonistAgeDifferenceTheme
chosen
Indicates that the work thematically explores the significance or impact of age differences involving the protagonist.
-
B.
portrayedByCharacterAgeApprox
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
C.
relativeAgeInference
Indicates an inferred ordering of ages between entities, specifying which one is relatively older or younger based on available information.
-
D.
ageInSeries
Indicates the age of an entity as it appears or is depicted within a specific series or installment of a work.
-
E.
spouseAgeDifference
Indicates the age gap between two individuals who are spouses in a marital relationship.
- 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_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:37 a.m.