Triple
T11713291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josephine Baker |
E278425
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Freda |
E415848
|
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: Freda | Statement: [Josephine Baker, givenName, Freda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freda Context triple: [Josephine Baker, givenName, Freda]
-
A.
Freda
chosen
Freda is a feminine given name, often used in English-speaking countries and derived from names like Winifred or Frederica.
-
B.
Frieda
Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
-
C.
Frieda
Frieda is a minor Peanuts character known for her naturally curly hair and prim personality, who appears alongside Charlie Brown and his friends.
-
D.
Frieda Falcon
Frieda Falcon is one of the costumed falcon mascots representing Bowling Green State University's athletic teams and school spirit.
-
E.
Fay
Fay is a given name most famously associated with Canadian-American actress Fay Wray, the iconic star of the 1933 film "King Kong."
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4be10088190854699385d1f6a95 |
completed | April 10, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f0196916e081908671e79765d03778 |
completed | April 28, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:40 p.m.