Triple
T14679688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leigh Russell |
E344744
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Leigh Russell |
E344744
|
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: Leigh Russell | Statement: [Leigh Russell, name, Leigh Russell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leigh Russell Context triple: [Leigh Russell, name, Leigh Russell]
-
A.
Leigh Russell
chosen
Leigh Russell is an Australian actress best known for her role in the controversial 1992 film "Romper Stomper."
-
B.
Diane Russell
Diane Russell is a complex, hard-edged yet vulnerable NYPD detective on the television drama "NYPD Blue," known for her struggles with alcoholism and tumultuous personal relationships.
-
C.
Rena Russell
Rena Russell was a film costume designer known for her work on the 1948 noir thriller "Hollow Triumph."
-
D.
Lea Hurst
Lea Hurst is a historic country house in Derbyshire, England, best known as the childhood home of Florence Nightingale.
-
E.
Kelly Roberts
Kelly Roberts is a businesswoman best known for owning and overseeing the historic Mission Inn Hotel & Spa in Riverside, California.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb5692284819090f775be8e478522 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8754ef408190be0e4ea5c35cf000 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 1:27 a.m.