Triple
T15122276
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Under the Mistletoe |
E361197
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Kuk Harrell |
E388130
|
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: Kuk Harrell | Statement: [Under the Mistletoe, producer, Kuk Harrell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kuk Harrell Context triple: [Under the Mistletoe, producer, Kuk Harrell]
-
A.
Kuk Harrell
chosen
Kuk Harrell is a Grammy-winning American vocal producer and songwriter best known for crafting and recording hit vocals for major pop and R&B artists such as Rihanna, Beyoncé, and Justin Bieber.
-
B.
Thaddis Harrell
Thaddis Harrell is a songwriter best known for co-writing the hit pop single "Never Say Never."
-
C.
Chauncey Winbush
Chauncey Winbush is a collegiate sports administrator who serves as the athletic director for the Rams athletic program.
-
D.
Makani Harrelson
Makani Harrelson is the daughter of American actor Woody Harrelson and his wife Laura Louie.
-
E.
Kene Holliday
Kene Holliday is an American actor best known for his role as investigator Tyler Hudson on the television series "Matlock."
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0059f69a881909929a037a0eef702 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed321d6108190a30b32f176e6d4dc |
completed | May 9, 2026, 6:24 a.m. |
Created at: April 10, 2026, 3:06 a.m.