Triple
T11458591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta Sue Ficker |
E271590
|
entity |
| Predicate | hasFamilyName |
P18
|
FINISHED |
| Object | Ficker |
E49208
|
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: Ficker | Statement: [Roberta Sue Ficker, hasFamilyName, Ficker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ficker Context triple: [Roberta Sue Ficker, hasFamilyName, Ficker]
-
A.
Ficker
chosen
Ficker is the birth surname of renowned American ballerina Suzanne Farrell, one of the most celebrated muses of choreographer George Balanchine.
-
B.
Fiser
Fiser is a surname variant of Fischer, commonly associated with Central or Eastern European origins.
-
C.
Frewer
Frewer is a surname most notably associated with Canadian-American actor Matt Frewer, known for portraying the character Max Headroom.
-
D.
Flecher
Flecher is a variant spelling of the surname Fletcher, which traditionally refers to a maker or seller of arrows.
-
E.
Fadden
Fadden is a residential suburb in the Canberra region of the Australian Capital Territory.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f2138081909408c7916cef99c9 |
completed | April 9, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e911c03c819081f1447b320dd2f2 |
completed | April 20, 2026, 8:51 a.m. |
Created at: April 8, 2026, 9:35 p.m.