Triple
T318397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbara |
E7758
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Barbra |
E7758
|
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: Barbra | Statement: [Barbara, hasVariant, Barbra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barbra Context triple: [Barbara, hasVariant, Barbra]
-
A.
Marilyn
A Marilyn is a type of British hill or mountain classified by having a prominence of at least 150 meters, regardless of its absolute height.
-
B.
Barbara
chosen
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
C.
Bette Midler
Bette Midler is an American singer, actress, and comedian renowned for her powerful vocals, theatrical performances, and acclaimed work in film, television, and on stage.
-
D.
Barbra Streisand
Barbra Streisand is an acclaimed American singer, actress, and filmmaker known for her powerful voice, award-winning performances, and enduring influence on popular culture.
-
E.
Gloria Vanderbilt
Gloria Vanderbilt was an American artist, socialite, fashion designer, and heiress renowned for her influential designer jeans line and prominent role in 20th-century high society.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea67b7588190be394a56498758b6 |
completed | Feb. 28, 2026, 1:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3d7e47f1c8190a4152dcb5c662514 |
completed | March 1, 2026, 6:08 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.