Triple
T21700150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Annenberg |
E535633
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Annenberg |
—
|
NE NERFINISHED |
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: Annenberg | Statement: [Walter Annenberg, familyName, Annenberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annenberg Context triple: [Walter Annenberg, familyName, Annenberg]
-
A.
Annenberg
chosen
Annenberg is a prominent American family name associated with influential figures in media, philanthropy, and public service.
-
B.
Doheny
Doheny is a surname most notably associated with Edward L. Doheny, an American oil tycoon and early petroleum industry pioneer.
-
C.
Pardee
Pardee is a surname most notably associated with George Pardee, a Progressive-era governor of California and public health advocate.
-
D.
Annenberg Foundation
The Annenberg Foundation is a major American family philanthropy that supports education, arts and culture, civic engagement, and social justice initiatives through grants and strategic investments.
-
E.
Kupferberg
Kupferberg is a small town in the Bavarian region of Germany, known for its historical charm and location within the Franconian landscape.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef9b7edd3c8190bca83ef37598cbfb |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 16, 2026, 6:45 p.m.