Triple
T13002706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Below Deck |
E322207
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Rebecca Taylor Henning |
E1022743
|
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: Rebecca Taylor Henning | Statement: [Below Deck, executiveProducer, Rebecca Taylor Henning]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rebecca Taylor Henning Context triple: [Below Deck, executiveProducer, Rebecca Taylor Henning]
-
A.
Rebecca Taylor Henning
chosen
Rebecca Taylor Henning is a television producer and writer best known for creating the reality TV series "Below Deck."
-
B.
Rebecca Harris
Rebecca Harris is a fictional character portrayed by Jennifer Carpenter, best known as the determined FBI agent in the television series "Limitless."
-
C.
Rebecca Blunt
Rebecca Blunt is a screenwriter best known for penning the heist comedy film "Logan Lucky."
-
D.
Rebecca Yeldham
Rebecca Yeldham is a film producer known for her work on acclaimed independent and international films, including the adaptation of "The Kite Runner."
-
E.
Rebecca Howe
Rebecca Howe is a fictional character on the sitcom "Cheers," known as the ambitious and often neurotic bar manager who replaces Diane Chambers.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9a2a448190968833354280e474 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d7cfe24819096e8f4cd496a6fd7 |
completed | May 3, 2026, 2:36 p.m. |
Created at: April 9, 2026, 8:47 p.m.