Triple
T20862298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Brodsky |
E513650
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Anna Brodsky |
—
|
NE NERFINISHED |
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: Anna Brodsky | Statement: [Joseph Brodsky, child, Anna Brodsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Brodsky Context triple: [Joseph Brodsky, child, Anna Brodsky]
-
A.
Anna Brodsky
chosen
Anna Brodsky is the daughter of Nobel Prize–winning Russian-American poet and essayist Joseph Brodsky.
-
B.
Valentina Brodsky
Valentina Brodsky was the second wife of renowned modernist painter Marc Chagall, with whom she spent his later years in France.
-
C.
Aliza Bloch
Aliza Bloch is an Israeli educator and politician who became the first female mayor of Beit Shemesh, noted for her efforts to bridge divides in the city's diverse population.
-
D.
Olga Loyev
Olga Loyev was the wife of the famed Yiddish writer Sholem Aleichem and a supportive partner throughout his literary career.
-
E.
Olga Loyev
Olga Loyev is a person whose specific public background or notable achievements are not clearly documented in widely available sources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4f5b01081909452f654d2fc3f50 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3ad3d1c8190be2fe35a85f2447c |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 12:44 p.m.