Triple
T16295884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taylor Dearden |
E395645
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Taylor Dearden |
E395645
|
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: Taylor Dearden | Statement: [Taylor Dearden, name, Taylor Dearden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taylor Dearden Context triple: [Taylor Dearden, name, Taylor Dearden]
-
A.
Taylor Dearden
chosen
Taylor Dearden is an American actress known for roles in series such as "Sweet/Vicious" and for being the daughter of actor Bryan Cranston.
-
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.
Julie Hayden
Julie Hayden was an American short story writer and journalist known for her acclaimed collection "The Lists of the Past" and her work at The New Yorker.
-
D.
Diane Lane
Diane Lane is an American actress acclaimed for her versatile performances in film and television, with a career spanning from childhood roles to major Hollywood productions.
-
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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2d08108190bab1b3325923af1d |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9b42248190a3c8c2647a42aeb9 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.