Triple
T6638803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brewster |
E150528
|
entity |
| Predicate | hasRelatedSurname |
P3889
|
FINISHED |
| Object | Brewer |
E572462
|
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: Brewer | Statement: [Brewster, hasRelatedSurname, Brewer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brewer Context triple: [Brewster, hasRelatedSurname, Brewer]
-
A.
Brewer
chosen
Brewer is a common English occupational surname originally given to people who brewed ale or beer.
-
B.
Brewer, Maine
Brewer, Maine is a small city in Penobscot County located across the Penobscot River from Bangor and functioning as part of the Bangor metropolitan area.
-
C.
Monaca
Monaca is a small borough located along the Ohio River in Beaver County, Pennsylvania, known historically for its industrial and riverfront character.
-
D.
Redhook
Redhook is a fiction-focused publishing imprint of Hachette Book Group known for commercial and genre titles.
-
E.
Brewster
Brewster is a small hamlet and census-designated place in Putnam County, New York, known for its historic downtown and role as a local commercial and transportation hub.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aff082b0819089f5a69aa67d5346 |
completed | March 27, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e453cb14819093597dda825b4304 |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 2 p.m.