Triple
T5578982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Bellows |
E146592
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | New York |
E40
|
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: New York | Statement: [George Bellows, notableWork, New York]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New York Context triple: [George Bellows, notableWork, New York]
-
A.
New York
New York is a populous and economically significant U.S. state known for New York City, a global center of finance, culture, and media.
-
B.
New York City
chosen
New York City is the largest city in the United States, a global center of finance, culture, media, and technology.
-
C.
Washington, New York
Washington, New York is a rural town in Dutchess County known for its historic hamlet of Millbrook, scenic landscapes, and equestrian and agricultural heritage.
-
D.
NYC
NYC is a historic American railroad company that operated major passenger and freight services across the northeastern and midwestern United States.
-
E.
Manhattan
The Manhattan is a classic whiskey-based cocktail, traditionally made with rye or bourbon, sweet vermouth, and bitters, and typically served stirred and garnished with a cherry.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0206bfea08190aa2c8df9f88013ac |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04ca8b17c8190a902917076367743 |
completed | March 22, 2026, 8:10 p.m. |
Created at: March 22, 2026, 3:37 p.m.