Triple
T7524793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscar de la Renta |
E177863
|
entity |
| Predicate | designedFor |
P98
|
FINISHED |
| Object | Hillary Rodham Clinton |
E7583
|
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: Hillary Rodham Clinton | Statement: [Oscar de la Renta, designedFor, Hillary Rodham Clinton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hillary Rodham Clinton Context triple: [Oscar de la Renta, designedFor, Hillary Rodham Clinton]
-
A.
Hillary Clinton
chosen
Hillary Clinton is an American politician and diplomat who served as U.S. Secretary of State, U.S. senator from New York, First Lady, and the first woman to be a major party’s presidential nominee.
-
B.
Hilary
Hilary is a given name most notably borne by the influential American philosopher Hilary Putnam.
-
C.
Katherine McKinley
Katherine McKinley was the daughter of U.S. President William McKinley and First Lady Ida Saxton McKinley, who died in childhood and is remembered primarily in the context of her parents' lives.
-
D.
Condoleezza
Condoleezza is the distinctive given name of Condoleezza Rice, the American political scientist and former U.S. Secretary of State.
-
E.
Mary Podesta
Mary Podesta is an American lawyer and privacy policy expert known for her work on data protection and technology issues, including senior roles in government and industry.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c61b508190b582f54ecbb387e3 |
completed | March 27, 2026, 9:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c84631e6bc819099b3a7819c3ae9a7 |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:46 p.m.