Triple
T31314109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Can Do It With a Broken Heart |
E798540
|
entity |
| Predicate | moodContrast |
P85805
|
FINISHED |
| Object | cheerful sound vs sad lyrics |
—
|
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: cheerful sound vs sad lyrics | Statement: [I Can Do It With a Broken Heart, moodContrast, cheerful sound vs sad lyrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: moodContrast Context triple: [I Can Do It With a Broken Heart, moodContrast, cheerful sound vs sad lyrics]
-
A.
moodContrastWithinWork
chosen
Indicates a contrast or shift between different moods or emotional tones within the same work.
-
B.
dramaticContrastWith
Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
-
C.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
-
D.
dramaticContrastType
Indicates a type of contrast between elements (such as characters, scenes, or ideas) that heightens drama or emotional impact.
-
E.
oftenContrastedWith
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
- 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_69f224e1932c81908fef14f7b03a10b7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:15 p.m.