Triple
T9395349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let 'Em In |
E226128
|
entity |
| Predicate | mentionsInLyrics |
P45526
|
FINISHED |
| Object | Uncle Ernie |
E242590
|
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: Uncle Ernie | Statement: [Let 'Em In, mentionsInLyrics, Uncle Ernie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uncle Ernie Context triple: [Let 'Em In, mentionsInLyrics, Uncle Ernie]
-
A.
Ernie
chosen
Ernie is a common diminutive form of the given name Ernest, often used as a familiar or affectionate nickname.
-
B.
Uncle Paul
Uncle Paul is an affectionate English nickname most famously associated with "Oom Paul," the popular moniker of South African Boer leader and former Transvaal president Paul Kruger.
-
C.
Uncle Bob
Uncle Bob is the nickname of Robert C. Martin, a prominent software engineer and author known for his influential work on clean code practices and agile software development.
-
D.
Uncle Albert
Uncle Albert is a fictional character from Paul and Linda McCartney’s song “Uncle Albert/Admiral Halsey,” representing a whimsical, nostalgic older relative.
-
E.
Grandpa Joe
Grandpa Joe is Charlie Bucket’s elderly, spirited grandfather who joins him on the fantastical tour of Willy Wonka’s chocolate factory in the 2005 film adaptation.
- 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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5112faa08190a8dd2c461d1e7a14 |
completed | April 1, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d10114e4d08190b4f465f9e56f9ffd |
completed | April 4, 2026, 12:16 p.m. |
Created at: March 30, 2026, 7:45 p.m.