Triple
T12839653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walter Brewster |
E307014
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Walter Brewster |
E307014
|
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: Walter Brewster | Statement: [Walter Brewster, name, Walter Brewster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walter Brewster Context triple: [Walter Brewster, name, Walter Brewster]
-
A.
Walter Brewster
chosen
Walter Brewster was a prominent local landowner and early settler after whom the Village of Brewster in New York was named.
-
B.
Walter Pitman
Walter Pitman was an American geophysicist and oceanographer known for his pioneering work on seafloor spreading and plate tectonics.
-
C.
Walter Gilman
Walter Gilman is the ill-fated Miskatonic University student whose occult studies and nightmarish experiences drive the plot of H. P. Lovecraft’s horror story "The Dreams in the Witch House."
-
D.
Walter March
Walter March was a German architect best known for designing Berlin’s Olympiastadion, the main venue of the 1936 Olympic Games.
-
E.
Arthur Aylesworth
Arthur Aylesworth was an American character actor known for his supporting roles in numerous Hollywood films during the 1930s and 1940s.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff11b4481909fb2f92c46186853 |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b9dc1e48190993430956e0fcfdc |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:35 p.m.