Triple
T20263450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rudy Langlais |
E498902
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Sugar Hill |
—
|
NE NERFINISHED |
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: Sugar Hill | Statement: [Rudy Langlais, notableWork, Sugar Hill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sugar Hill Context triple: [Rudy Langlais, notableWork, Sugar Hill]
-
A.
Sugar Hill
chosen
Sugar Hill is a 1993 crime drama film set in Harlem that follows two brothers navigating the dangers of the drug trade and family loyalty.
-
B.
Sugar Hill
Sugar Hill is a historic, culturally significant neighborhood in Upper Manhattan, New York City, long associated with the Harlem Renaissance and African-American arts and intellectual life.
-
C.
Sugar Hill
Sugar Hill is a suburban city in Gwinnett County, Georgia, known as part of the greater Atlanta metropolitan area.
-
D.
Sun Hill
Sun Hill is the fictional London police station that serves as the central setting for the long-running British television drama "The Bill."
-
E.
Harlem Streets
"Harlem Streets" is a socially conscious hip-hop track by rapper Cam'ron from his 2004 album *Purple Haze*, depicting life and struggles in Harlem.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da6275fa6c8190952924930adee150 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e674ccff008190920b418f51dc4311 |
completed | April 20, 2026, 6:47 p.m. |
Created at: April 11, 2026, 11:41 p.m.