Triple
T15584241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lucky Louie |
E374576
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Kim Hawthorne |
E774926
|
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: Kim Hawthorne | Statement: [Lucky Louie, portrayedBy, Kim Hawthorne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kim Hawthorne Context triple: [Lucky Louie, portrayedBy, Kim Hawthorne]
-
A.
Kim Hawthorne
chosen
Kim Hawthorne is an American actress best known for her prominent role on the Oprah Winfrey Network drama series "Greenleaf."
-
B.
Denys Hawthorne
Denys Hawthorne was a Northern Irish actor known for his work in British television, film, and theatre.
-
C.
Frank Sanborn
Frank Sanborn was a 19th-century American abolitionist, journalist, and reformer closely associated with the Transcendentalist movement and figures such as John Brown and Ralph Waldo Emerson.
-
D.
Frank Sanborn
Frank Sanborn is an entrepreneur best known as the founder of the Sanborns retail and restaurant chain.
-
E.
Nathan Dane
Nathan Dane was an American lawyer and statesman best known for drafting the Northwest Ordinance of 1787, which shaped the early expansion and governance of the United States.
- 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_69d85ccd575081908909b71a3f3e3a61 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e47971481909e986dd999354628 |
completed | April 16, 2026, 2:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4f71e48190a15eb0a2138f083f |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:11 a.m.