Triple
T16695370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blink-182 |
E405701
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Dammit |
E399225
|
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: Dammit | Statement: [Blink-182, notableSong, Dammit]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dammit Context triple: [Blink-182, notableSong, Dammit]
-
A.
Dammit
chosen
"Dammit" is a fast-paced pop-punk song by Blink-182, widely recognized as one of their breakout hits from the late 1990s.
-
B.
Damn It, Rose
"Damn It, Rose" is an episode of the animated sci-fi comedy series "Inside Job," which follows the dysfunctional employees of a shadowy organization that secretly runs the world.
-
C.
Gat Damn
"Gat Damn" is a hip-hop track best known for its association with the artist Bandana and its hard-hitting, street-influenced style.
-
D.
Damn!
"Damn!" is a 2003 crunk/hip-hop single by YoungBloodZ featuring Lil Jon, best known for its aggressive energy and memorable hook that made it a club and radio hit.
-
E.
Hot Damn
Hot Damn is a hip hop song by Clipse known for its gritty production and sharp, boastful lyricism.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37eacfa788190a8d2058f96c0d445 |
completed | April 18, 2026, 12:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00919acd308190a3f29040554b9cfc |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.