Triple
T5063154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta Sue Ficker |
E114074
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Roberta |
E28738
|
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: Roberta | Statement: [Roberta Sue Ficker, hasGivenName, Roberta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberta Context triple: [Roberta Sue Ficker, hasGivenName, Roberta]
-
A.
Roberta
chosen
Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
-
B.
Roberta
"Roberta" is a 1935 Hollywood musical film starring Fred Astaire (Frederick Austerlitz) and Ginger Rogers, known for its fashion-world setting and classic Jerome Kern songs.
-
C.
Joanne
Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
-
D.
Roberta Martin
Roberta Martin is a central childhood friend in the coming-of-age film "Now and Then," known for her tomboyish personality and strong, loyal nature within the group.
-
E.
Rita
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
- 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7475be3c819085cde8ec544c407e |
completed | March 20, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea497fed0819098746fd8917f041c |
completed | March 21, 2026, 2 p.m. |
Created at: March 20, 2026, 1:38 p.m.