Triple
T507311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruth Bader Ginsburg |
E10528
|
entity |
| Predicate | maidenName |
P18
|
FINISHED |
| Object | Bader |
E10528
|
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: Bader | Statement: [Ruth Bader Ginsburg, maidenName, Bader]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bader Context triple: [Ruth Bader Ginsburg, maidenName, Bader]
-
A.
Bader
chosen
Bader is the maiden surname of Ruth Bader Ginsburg, the late U.S. Supreme Court Justice and pioneering advocate for gender equality.
-
B.
Erwin
Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
-
C.
Durkan
Durkan is a surname most notably associated with Jenny Durkan, the former mayor of Seattle and an American attorney and politician.
-
D.
Konrad
Konrad is a masculine given name of German origin, historically borne by several notable figures including statesmen, nobles, and religious leaders.
-
E.
Koba
Koba was a revolutionary alias used by Joseph Stalin during his early political activities in the Bolshevik movement.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f14dcd688190ad47a3b31b95b6d4 |
completed | Feb. 28, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a498506418819090190a35e8763982 |
completed | March 1, 2026, 7:49 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.