Triple
T13810361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arizona (2018 film) |
E331871
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Tia Nolan |
E453078
|
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: Tia Nolan | Statement: [Arizona (2018 film), editedBy, Tia Nolan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tia Nolan Context triple: [Arizona (2018 film), editedBy, Tia Nolan]
-
A.
Tia Nolan
chosen
Tia Nolan is a film editor known for her work on major studio comedies and feature films, including the romantic comedy "Friends with Benefits."
-
B.
Jennifer Tighe
Jennifer Tighe is an American actress known for her work in television, film, and theater, and as the daughter of actor Kevin Tighe.
-
C.
Tara Conway
Tara Conway is a person whose specific public background or notable achievements are not clearly identifiable from the given information.
-
D.
Beth Nolan
Beth Nolan is an American lawyer and legal scholar who served as White House Counsel to President Bill Clinton.
-
E.
Jessica Keenan Wynn
Jessica Keenan Wynn is an American actress and singer best known for her work in musical theatre and for playing the younger version of Tanya in the film "Mamma Mia! Here We Go Again."
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de026ff6b481908066d6bf27064417 |
completed | April 14, 2026, 9:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac7e59188190ad28707ba363e341 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 10:12 p.m.