Triple
T1335504
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta |
E28738
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Bobbi |
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: Bobbi | Statement: [Roberta, hasDiminutive, Bobbi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bobbi Context triple: [Roberta, hasDiminutive, Bobbi]
-
A.
Betty
Betty is the childhood nickname of Elizabeth Parris, the young girl whose strange afflictions helped spark the Salem witch trials in 1692.
-
B.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
C.
Peggy
Peggy is a common diminutive or nickname for the given name Margaret.
-
D.
Marcia
Marcia was the mother of the Roman emperor Trajan and a member of the provincial Roman aristocracy in Hispania.
-
E.
Roberta
chosen
Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc62b9bd081909dbe22cbea03f21f |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:55 p.m.