Triple
T15415612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | B-Real |
E369217
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Dr. Greenthumb |
E784480
|
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: Dr. Greenthumb | Statement: [B-Real, alsoKnownAs, Dr. Greenthumb]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dr. Greenthumb Context triple: [B-Real, alsoKnownAs, Dr. Greenthumb]
-
A.
Dr. Greenthumb
chosen
"Dr. Greenthumb" is a popular 1998 hip-hop song by Cypress Hill, known for its humorous, cannabis-themed lyrics and distinctive persona created by rapper B-Real.
-
B.
Dr. Green
Dr. Green is a minor supporting character in the 1997 romantic comedy-drama film "As Good as It Gets."
-
C.
Professor Green
Professor Green is a British rapper and songwriter known for his witty lyricism, chart-topping singles, and appearances on UK television.
-
D.
Doc Hopper
Doc Hopper is the main antagonist in The Muppet Movie, a ruthless fast-food magnate obsessed with forcing Kermit the Frog to promote his chain of frog leg restaurants.
-
E.
Dr. Scarabus
Dr. Scarabus is the powerful and sinister sorcerer antagonist in the 1963 horror-comedy film "The Raven."
- 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_69d85a1849f48190bf898068b2806fae |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03ea8a8a081909749db1b29d85fcc |
completed | April 16, 2026, 1:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a7722a08190af230ecafda30b18 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:20 a.m.