Triple
T16569271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasha Kropinski |
E402541
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kropinski |
E402541
|
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: Kropinski | Statement: [Kasha Kropinski, familyName, Kropinski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kropinski Context triple: [Kasha Kropinski, familyName, Kropinski]
-
A.
Kropinski
chosen
Kropinski is a surname most notably associated with South African-born actress Kasha Kropinski.
-
B.
Kurnitz
Kurnitz is a surname most notably associated with American playwright and screenwriter Harry Kurnitz.
-
C.
Krislov
Krislov is a surname most notably associated with Marvin Krislov, an American academic administrator and university president.
-
D.
Kopaska
Kopaska is the Indonesian Navy’s elite frogman and special operations unit, specializing in underwater demolition, maritime sabotage, and counter-terrorism missions.
-
E.
Kopervik
Kopervik is a coastal town in Rogaland county, Norway, situated on the island of Karmøy and serving as an important local commercial and administrative center.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35773c00c819091731bebc02a69bb |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00759424348190889dacbbc7435238 |
completed | May 10, 2026, 12:09 p.m. |
Created at: April 10, 2026, 5:16 a.m.