Triple
T15761243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Too Good at Goodbyes |
E382100
|
entity |
| Predicate | labelGenreCategory |
P93135
|
FINISHED |
| Object | contemporary pop ballad |
—
|
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: contemporary pop ballad | Statement: [Too Good at Goodbyes, labelGenreCategory, contemporary pop ballad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelGenreCategory Context triple: [Too Good at Goodbyes, labelGenreCategory, contemporary pop ballad]
-
A.
keyGenreFilm
Indicates that a particular genre is the primary or defining genre associated with a given film.
-
B.
targetGenre
Indicates the genre that something is specifically aimed at, categorized under, or intended to belong to.
-
C.
tvGenre
Indicates the genre or category to which a television show or program belongs.
-
D.
visualGenre
Indicates the visual or stylistic category to which something belongs, such as its artistic or cinematic genre.
-
E.
musicGenreCategory
chosen
Indicates that one entity is a broader music genre category under which the other music genre is classified.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b52c548190a0ffa4493a4eb15c |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.