Triple
T2059581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amawalk (part) |
E45756
|
entity |
| Predicate | town |
P3385
|
FINISHED |
| Object | Yorktown |
E85796
|
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: Yorktown | Statement: [Amawalk (part), town, Yorktown]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yorktown Context triple: [Amawalk (part), town, Yorktown]
-
A.
Yorktown
Yorktown is a historic American town best known as the site of the decisive 1781 Revolutionary War battle that effectively ended British rule in the Thirteen Colonies.
-
B.
Williamsburg
Williamsburg is a historic colonial city in Virginia renowned for its well-preserved 18th-century architecture and living-history museum, Colonial Williamsburg.
-
C.
Williamsburg
Williamsburg is a trendy Brooklyn neighborhood known for its vibrant arts scene, nightlife, and waterfront views of Manhattan.
-
D.
Yorktown, New York
chosen
Yorktown, New York is a suburban town in the Hudson Valley region north of New York City, known for its residential communities, parks, and historic sites.
-
E.
Lafayette
Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9cfdac88190b8b7af1bfea6a78e |
completed | March 7, 2026, 5:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae271cb26c81908664f4c26f4fb5ea |
completed | March 9, 2026, 1:49 a.m. |
Created at: March 4, 2026, 7:40 p.m.