Triple
T12869692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jennifer Michelle Goodwin |
E307815
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Goodwin |
E307816
|
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: Goodwin | Statement: [Jennifer Michelle Goodwin, familyName, Goodwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goodwin Context triple: [Jennifer Michelle Goodwin, familyName, Goodwin]
-
A.
Goodwin
Goodwin is a masculine given name most notably borne by Goodwin Knight, who served as the 31st governor of California in the mid-20th century.
-
B.
Goodwin
chosen
Goodwin is the surname of American actress Ginnifer Goodwin, known for her roles in "Once Upon a Time" and "Big Love."
-
C.
Winston & Strawn
Winston & Strawn is a major international law firm headquartered in Chicago, known for its litigation, corporate, and regulatory practices.
-
D.
Arnall
Arnall is a surname most notably associated with Roland Arnall, a billionaire businessman and former U.S. Ambassador to the Netherlands.
-
E.
Greenlaw
Greenlaw is a small historic town in the Scottish Borders that once served as the county town of Berwickshire.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970905784819091631161a9de98c5 |
completed | April 10, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb26eb08190912d0b44c345bf41 |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:38 p.m.