Triple
T1005768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Who Wants to Be a Millionaire? |
E21706
|
entity |
| Predicate | lyricalTone |
P9652
|
FINISHED |
| Object | witty |
—
|
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: witty | Statement: [Who Wants to Be a Millionaire?, lyricalTone, witty]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lyricalTone Context triple: [Who Wants to Be a Millionaire?, lyricalTone, witty]
-
A.
lyricalPerspective
Indicates the narrative or point of view from which lyrics are expressed in a song or vocal piece.
-
B.
hasLyricalStyle
chosen
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
C.
hasLyricalTheme
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
D.
lyricSetting
Indicates that one entity serves as the text or lyrics that are set to music or otherwise musically realized by another entity.
-
E.
notableSongCharacteristic
Indicates that a song is distinguished by a particular notable feature or quality, such as style, structure, or performance trait.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51303548190a5ee3c0797fc3245 |
completed | March 1, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b2e7108190b338b6c19d4aff55 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.