Triple
T8572532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamara Tunie |
E202961
|
entity |
| Predicate | characterPlayed |
P1507
|
FINISHED |
| Object | Melinda Warner |
E742497
|
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: Melinda Warner | Statement: [Tamara Tunie, characterPlayed, Melinda Warner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melinda Warner Context triple: [Tamara Tunie, characterPlayed, Melinda Warner]
-
A.
Melinda Warner
chosen
Melinda Warner is the dedicated and highly skilled medical examiner on the television series "Law & Order: Special Victims Unit."
-
B.
Katherine Spiegel
Katherine Spiegel was the wife of prominent American film director and producer Mervyn LeRoy.
-
C.
Mimi Rogers
Mimi Rogers is an American actress and former model known for her work in film and television since the 1980s, including notable roles in movies like "The Rapture" and "Austin Powers: International Man of Mystery."
-
D.
Melinda Washington
Melinda Washington is the child of Joshua Washington, known primarily in relation to him.
-
E.
Sandra McCabe
Sandra McCabe is an actress known for her role in the film "The Rose."
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea43843c8190ac2224d427bb7a75 |
completed | March 31, 2026, 3:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cebb8e8b9481908f7096acefaa0ffd |
completed | April 2, 2026, 6:55 p.m. |
Created at: March 30, 2026, 6:21 p.m.