Triple
T14398356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirty Sexy Money |
E357007
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Natalie Zea |
E836044
|
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: Natalie Zea | Statement: [Dirty Sexy Money, starring, Natalie Zea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Natalie Zea Context triple: [Dirty Sexy Money, starring, Natalie Zea]
-
A.
Natalie Zea
chosen
Natalie Zea is an American actress best known for her television work in series such as Justified, The Following, and The Detour.
-
B.
Alice Patten
Alice Patten is a British actress best known internationally for her role as an English documentary filmmaker in the acclaimed Indian film "Rang De Basanti."
-
C.
Melissa Hudson
Melissa Hudson is known as the daughter of Stanley Hudson, a character from the American television series "The Office."
-
D.
Tiffani Thiessen
Tiffani Thiessen is an American actress best known for her roles on the television series "Saved by the Bell" and "Beverly Hills, 90210."
-
E.
Rebecca Washington
Rebecca Washington is a central character on the legal drama series "The Practice," known for her work as a dedicated attorney at the show's featured law firm.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9083f9d081908fe5c99655c410b3 |
completed | April 14, 2026, 7:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe967e9c208190a00a82122b8c884c |
completed | May 9, 2026, 2:05 a.m. |
Created at: April 10, 2026, 1:17 a.m.