Triple
T11094008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Good Nurse |
E262326
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Nnamdi Asomugha |
E529129
|
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: Nnamdi Asomugha | Statement: [The Good Nurse, stars, Nnamdi Asomugha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nnamdi Asomugha Context triple: [The Good Nurse, stars, Nnamdi Asomugha]
-
A.
Nnamdi Asomugha
chosen
Nnamdi Asomugha is a former NFL cornerback, best known for his standout years with the Oakland Raiders and later work as a film producer and actor.
-
B.
Champ Bailey
Champ Bailey is a Pro Football Hall of Fame cornerback widely regarded as one of the greatest defensive backs in NFL history.
-
C.
Jermaine Stegall
Jermaine Stegall is an American film composer and conductor known for scoring major studio projects, including the soundtrack for the comedy sequel "Coming 2 America."
-
D.
Ada Foah
Ada Foah is a coastal town in southeastern Ghana known for its beaches, estuary scenery, and role as a local fishing and tourism center.
-
E.
Scott Hogsett
Scott Hogsett is an American wheelchair rugby player known for his prominent role on the U.S. Paralympic team and his appearance in the documentary film "Murderball."
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799ed12d88190a4ad8c346d68f11f |
completed | April 9, 2026, 12:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e7e0c7e4819098e690ffebbd8e61 |
completed | April 18, 2026, 8:21 p.m. |
Created at: April 8, 2026, 9:27 p.m.