Triple
T20517620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Woodcock |
E503720
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Melissa Sagemiller |
—
|
NE NERFINISHED |
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: Melissa Sagemiller | Statement: [Mr. Woodcock, starring, Melissa Sagemiller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melissa Sagemiller Context triple: [Mr. Woodcock, starring, Melissa Sagemiller]
-
A.
Melissa Sagemiller
chosen
Melissa Sagemiller is an American actress known for her work in film and television, including roles in projects like "The Guardian" and "Law & Order: Special Victims Unit."
-
B.
Melissa Ross
Melissa Ross is a television producer known for her work on the home design and lifestyle program "Ideal Home."
-
C.
Melissa Canaday
Melissa Canaday is an American actress and the mother of Modern Family star Sarah Hyland.
-
D.
Melissa Parmenter
Melissa Parmenter is a British composer and producer known for her film scores and frequent collaborations with director Michael Winterbottom.
-
E.
Melissa Sasse
Melissa Sasse is the wife of American academic and former U.S. Senator Ben Sasse and a longtime partner in his political and professional life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b2aa788190ae9eb37c1d73b1f1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f42db688190a3ccfba5601e8bf3 |
completed | April 20, 2026, 9:48 p.m. |
Created at: April 16, 2026, 11:36 a.m.