Triple
T13618392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Orlovsky |
E325384
|
entity |
| Predicate | sibling |
P363
|
FINISHED |
| Object | Marie Orlovsky |
E325384
|
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: Marie Orlovsky | Statement: [Peter Orlovsky, sibling, Marie Orlovsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie Orlovsky Context triple: [Peter Orlovsky, sibling, Marie Orlovsky]
-
A.
Marie Orlovsky
chosen
Marie Orlovsky is a member of the Orlovsky family, known primarily as the sister of Beat Generation poet Peter Orlovsky.
-
B.
Katherine Orlovsky
Katherine Orlovsky is the child of Beat Generation poet Peter Orlovsky.
-
C.
Alisa Freindlich
Alisa Freindlich is a renowned Soviet and Russian actress celebrated for her work in film and theater, particularly in the late 20th century.
-
D.
Tatiana Schlossberg
Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
-
E.
Juliana Minsky
Juliana Minsky is a member of the Minsky family, related to Henry Minsky and connected to the legacy of computer scientist Marvin Minsky.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0ae77e0819081e3b14642460dc6 |
completed | April 12, 2026, 2:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77fa0b81c819094e2fa209ef9857c |
completed | May 3, 2026, 5:02 p.m. |
Created at: April 9, 2026, 9:50 p.m.