Triple
T18642623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miroslava Federer |
E455726
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Myla Rose Federer |
—
|
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: Myla Rose Federer | Statement: [Miroslava Federer, child, Myla Rose Federer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myla Rose Federer Context triple: [Miroslava Federer, child, Myla Rose Federer]
-
A.
Miroslava Federer
chosen
Miroslava Federer is a former Slovak-born Swiss professional tennis player and the wife of tennis legend Roger Federer.
-
B.
Vanessa Nadal
Vanessa Nadal is a chemical engineer and lawyer who works in intellectual property law and is married to composer and playwright Lin-Manuel Miranda.
-
C.
Alexa Kenin
Alexa Kenin was an American film and television actress known for her supporting roles in 1980s movies such as "Pretty in Pink" and "Little Darlings."
-
D.
Heidi Zurbriggen
Heidi Zurbriggen is a former Swiss alpine skier who competed at the international level in the late 20th century.
-
E.
Elia Zurbriggen
Elia Zurbriggen is a Swiss alpine skier known for competing in international skiing competitions.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fcd6da081908030b052727f2c2f |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 10, 2026, 11:47 a.m.