Triple
T12202002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gangster and a Gentleman |
E290737
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | I Get High |
E290736
|
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: I Get High | Statement: [Gangster and a Gentleman, hasPart, I Get High]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Get High Context triple: [Gangster and a Gentleman, hasPart, I Get High]
-
A.
I Get High
chosen
"I Get High" is a popular hip-hop single by rapper Styles P, best known for its smooth, soulful production and its candid celebration of marijuana use.
-
B.
U Get Me High
"U Get Me High" is a rock song by Tom Petty and the Heartbreakers, featured on their 2014 album *Hypnotic Eye*.
-
C.
How High
How High is a 2001 stoner comedy film starring Method Man and Redman as underachieving friends who use a supernatural strain of marijuana to succeed at Harvard University.
-
D.
When on High
"When on High" is the traditional English rendering of the opening words and common title of the ancient Babylonian creation epic Enuma Elish.
-
E.
Baby Get Higher
"Baby Get Higher" is a pop song best known through Dutch singer Roel van Velzen’s rendition, which brought the track widespread recognition in the mid-2000s.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c7b97408190a11ea37cc6edf18c |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e549e688190967c00f437a388db |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:51 p.m.