Triple
T12000960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kima Greggs |
E285658
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Sonja Sohn |
E735056
|
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: Sonja Sohn | Statement: [Kima Greggs, portrayedBy, Sonja Sohn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sonja Sohn Context triple: [Kima Greggs, portrayedBy, Sonja Sohn]
-
A.
Sonja Sohn
chosen
Sonja Sohn is an American actress and filmmaker best known for her role as Detective Kima Greggs on the acclaimed television series "The Wire."
-
B.
Laura Sohn
Laura Sohn is an American actress best known for her role as FBI agent Alina Park on the television series "The Blacklist."
-
C.
Sandra Chung
Sandra Chung is an American linguist known for her influential work on syntax, Austronesian languages, and the interface between grammar and semantics.
-
D.
Myung-wha Chung
Myung-wha Chung is a renowned South Korean cellist recognized for her international concert career and collaborations with major orchestras and chamber ensembles.
-
E.
Linda Park
Linda Park is a Korean-American actress best known for playing communications officer Hoshi Sato on the television series Star Trek: Enterprise.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c26d7881909b67a31d04882eb5 |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4729eb4a081909d93b3fc74509d86 |
completed | May 1, 2026, 9:30 a.m. |
Created at: April 8, 2026, 9:46 p.m.