Triple
T6502225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Shot |
E148914
|
entity |
| Predicate | hasLyricalSubject |
P4921
|
FINISHED |
| Object | emotional distance in a relationship |
—
|
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: emotional distance in a relationship | Statement: [Cold Shot, hasLyricalSubject, emotional distance in a relationship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLyricalSubject Context triple: [Cold Shot, hasLyricalSubject, emotional distance in a relationship]
-
A.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
B.
hasLyricalForm
Indicates that one entity (typically a musical or poetic work) possesses or is characterized by a particular lyrical structure or form.
-
C.
hasLyricalStyle
Indicates that one entity possesses or is characterized by a particular lyrical style in relation to another entity or context.
-
D.
hasLyricsTheme
Indicates that the lyrics of a work primarily concern or revolve around a specified theme or subject.
-
E.
hasLyric
Indicates that one entity (typically a musical work or track) contains or is associated with the lyrics provided by another entity.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c69f386aa08190bfc8592a92ec6339 |
completed | March 27, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69c68ab714908190aa7c2fbf64078e15 |
completed | March 27, 2026, 1:48 p.m. |
Created at: March 27, 2026, 1:42 p.m.