Triple
T3933172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicky Barnes |
E90842
|
entity |
| Predicate | mediaNickname |
P17599
|
FINISHED |
| Object | Mr. Untouchable |
E399634
|
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: Mr. Untouchable | Statement: [Nicky Barnes, mediaNickname, Mr. Untouchable]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Untouchable Context triple: [Nicky Barnes, mediaNickname, Mr. Untouchable]
-
A.
Mr. Untouchable
chosen
Mr. Untouchable is the notorious nickname of Nicky Barnes, a powerful Harlem drug kingpin who dominated New York City's heroin trade in the 1970s.
-
B.
Untouchable
"Untouchable" is a hard-hitting hip-hop track by Pusha T known for its gritty lyricism and dark, minimalist production.
-
C.
The Mister
The Mister is a contemporary romance novel by E. L. James, known for its Cinderella-style love story and for being her follow-up to the Fifty Shades series.
-
D.
Mr. Five Percent
Mr. Five Percent is the nickname of Calouste Gulbenkian, an influential Armenian-British oil magnate and philanthropist who played a key role in shaping the early global petroleum industry.
-
E.
Touch the Devil
Touch the Devil is a Cold War-era thriller novel by Jack Higgins featuring espionage, terrorism, and high-stakes covert operations.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcab1808190bf653f29062cdddb |
completed | March 9, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5338afa348190bc5ac0b0319c6e45 |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:23 p.m.