Triple
T13633194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Rose |
E325777
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | William Rose |
E325777
|
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: William Rose | Statement: [William Rose, name, William Rose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Rose Context triple: [William Rose, name, William Rose]
-
A.
William Rose
chosen
William Rose was an American screenwriter best known for his work on classic comedies such as "The Russians Are Coming, the Russians Are Coming" and "Guess Who's Coming to Dinner."
-
B.
Charles Gillibert
Charles Gillibert is a French film producer known for backing acclaimed auteur-driven films such as "Clouds of Sils Maria," "Personal Shopper," and "Mustang."
-
C.
Thomas Mayne
Thomas Mayne was an Australian food scientist best known for creating the chocolate malted milk drink Milo in the 1930s.
-
D.
William Irwin
William Irwin was a 19th-century American politician who served as Governor of California from 1875 to 1880.
-
E.
William March
William March was an American author best known for his 1954 psychological horror novel "The Bad Seed," which became a classic of the genre and inspired multiple adaptations.
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc5a490508190924ac40f1dd519d6 |
completed | April 12, 2026, 4:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b05f0e948190b7f22d071ad54283 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 9:51 p.m.