Triple
T10404473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Morale & the Big Steppers |
E245226
|
entity |
| Predicate | precededBy |
P97
|
FINISHED |
| Object | DAMN. |
E245225
|
NE 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: DAMN. | Statement: [Mr. Morale & the Big Steppers, precededBy, DAMN.]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DAMN. Context triple: [Mr. Morale & the Big Steppers, precededBy, DAMN.]
-
A.
DAMN.
chosen
DAMN. is a critically acclaimed 2017 studio album by Kendrick Lamar that blends introspective lyricism with innovative production and won the Pulitzer Prize for Music.
-
B.
Dammit
"Dammit" is a fast-paced pop-punk song by Blink-182, widely recognized as one of their breakout hits from the late 1990s.
-
C.
Hot Damn
Hot Damn is a hip hop song by Clipse known for its gritty production and sharp, boastful lyricism.
-
D.
Don't Damn Me
"Don't Damn Me" is a hard rock song by Guns N' Roses, known for its aggressive vocals and introspective, confrontational lyrics.
-
E.
Dilla Dawg
Dilla Dawg is an alias of J Dilla, the influential American hip-hop producer and rapper known for his innovative, soulful beat-making.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9e5fb58819081d7d3e1dc625197 |
completed | April 7, 2026, 11:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d89f7bfce881908239cbb0915a5b81 |
completed | April 10, 2026, 6:58 a.m. |
Created at: April 6, 2026, 12:08 p.m.