Triple
T25568107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | When We Are Married |
E640892
|
entity |
| Predicate | hasDramaticIrony |
P140237
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [When We Are Married, hasDramaticIrony, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDramaticIrony Context triple: [When We Are Married, hasDramaticIrony, yes]
-
A.
dramaticIrony
chosen
Indicates a situation where the audience or reader knows critical information that one or more characters do not, creating a contrast between character perception and reality.
-
B.
hasDramaticPurpose
Indicates that something serves a specific dramatic function or role within a narrative or performance.
-
C.
hasIronicMeaning
Indicates that something conveys a meaning opposite to or incongruent with its literal expression, creating an ironic effect.
-
D.
hasDramaticRelief
Indicates that one entity provides or contains a moment or element that eases tension or emotional intensity within another entity or context.
-
E.
hasDramaticElements
Indicates that something contains features or qualities characteristic of drama, such as heightened emotion, tension, or conflict.
- 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_69e75dc1beb08190bac7d76b8d6e7bc4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8fe0abc8190862167a5d282e107 |
completed | May 2, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 3:50 p.m.