Triple
T38238078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | My White Knight |
E1013677
|
entity |
| Predicate | contrastWithSong |
P11289
|
FINISHED |
| Object | Goodnight, My Someone |
—
|
NE NERFINISHED |
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: Goodnight, My Someone | Statement: [My White Knight, contrastWithSong, Goodnight, My Someone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastWithSong Context triple: [My White Knight, contrastWithSong, Goodnight, My Someone]
-
A.
contrastUse
Indicates that one entity is used in opposition or distinction to another to highlight differences between them.
-
B.
genreContrast
Indicates a relationship where two or more works are compared or juxtaposed based on differences between their genres.
-
C.
contrastGoal
Indicates a relationship where one goal is defined in opposition to, or as a contrasting alternative to, another goal.
-
D.
dramaticContrastWith
Indicates that one entity is presented in a way that sharply emphasizes differences in tone, style, or impact when compared with another entity.
-
E.
oftenContrastedWith
chosen
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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
Created at: May 3, 2026, 4:30 p.m.