Triple
T34137499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apparently |
E875606
|
entity |
| Predicate | hasNotableLyricSubject |
P4921
|
FINISHED |
| Object | J. Cole's mother |
—
|
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: J. Cole's mother | Statement: [Apparently, hasNotableLyricSubject, J. Cole's mother]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLyricSubject Context triple: [Apparently, hasNotableLyricSubject, J. Cole's mother]
-
A.
hasNotableSubject
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
B.
hasLyricsMentioning
Indicates that the referenced lyrics explicitly mention or refer to the specified entity.
-
C.
hasMemorableLyric
Indicates that something (such as a song, verse, or musical piece) contains a lyric that is especially striking, distinctive, or easy to remember.
-
D.
hasLyricalTheme
chosen
Indicates that one entity (typically a creative work) features or is characterized by a particular lyrical subject, topic, or theme.
-
E.
hasNotableSongFeature
Indicates that one entity (typically a song) includes a significant or noteworthy contribution, appearance, or characteristic involving 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_69f349aaeef08190a20e72a3fdeb7052 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a02ff7de1d881909c29729f2a771381 |
completed | May 12, 2026, 10:22 a.m. |
| PD | Predicate disambiguation | batch_6a02fd1c45c48190bf9dbd91acaeee9f |
completed | May 12, 2026, 10:12 a.m. |
Created at: May 1, 2026, 1:53 a.m.