Triple
T17435984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oh My Darling, Clementine |
E424002
|
entity |
| Predicate | isFrequentlyAdaptedAs |
P22743
|
FINISHED |
| Object | cartoon musical segment |
—
|
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: cartoon musical segment | Statement: [Oh My Darling, Clementine, isFrequentlyAdaptedAs, cartoon musical segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequentlyAdaptedAs Context triple: [Oh My Darling, Clementine, isFrequentlyAdaptedAs, cartoon musical segment]
-
A.
isFrequentlyAdapted
chosen
Indicates that a work or source material is often transformed or re-created into new formats or versions, such as films, plays, or other media.
-
B.
hasHumanAdaptation
Indicates that something has been modified, designed, or adjusted specifically to suit human use, abilities, or needs.
-
C.
isAdaptation
Indicates that one work is derived from, based on, or reinterprets the content of another work.
-
D.
isFrequently
Indicates that an action, state, or relationship occurs often or with high regularity between the related entities.
-
E.
adaptationType
Indicates the specific kind or category of adaptation that relates one entity to another or to a particular context.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4490426008190b474ed76aca5d6f3 |
completed | April 19, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69e3b030eac481909b8402719cc3102e |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:46 a.m.