Triple
T15594168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gotta Get Through Another Day |
E374829
|
entity |
| Predicate | hasWriterOccupation |
P938
|
FINISHED |
| Object | singer-songwriter |
—
|
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: singer-songwriter | Statement: [Gotta Get Through Another Day, hasWriterOccupation, singer-songwriter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWriterOccupation Context triple: [Gotta Get Through Another Day, hasWriterOccupation, singer-songwriter]
-
A.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
B.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
C.
authorOccupation
chosen
Indicates the professional role or job that an author holds or is associated with.
-
D.
hasOccupationDuringStory
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
-
E.
dedicatedToOccupation
Indicates that an entity is committed or devoted to performing or pursuing a particular occupation or professional role.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5e43d48190a8fd367f13f1c7e1 |
completed | April 16, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69deda817e9881909b0c66fc9056f7d5 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:12 a.m.