Triple
T23541877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Level Canal |
E577773
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Holyoke |
—
|
NE NERFINISHED |
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: Holyoke | Statement: [Second Level Canal, city, Holyoke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holyoke Context triple: [Second Level Canal, city, Holyoke]
-
A.
Holyoke, Massachusetts
chosen
Holyoke, Massachusetts is a historic industrial city in western Massachusetts known for its early planned mill town design and significant role in the paper manufacturing industry.
-
B.
Lowell
Lowell is a surname most prominently associated with former Major League Baseball third baseman and World Series MVP Mike Lowell.
-
C.
Watertown
Watertown is a principal city in northeastern South Dakota known as a regional commercial center and home to Lake Kampeska and the Redlin Art Center.
-
D.
Watertown
Watertown is a small city in Wilson County, Tennessee, known for its historic downtown and role as a regional community hub.
-
E.
Watertown
Watertown is a small American city governed under a council–manager system, with a professional city manager overseeing its municipal operations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245f9d5d08190a4a20004e1784e20 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ae1cb8b48190b51dd83b9fb116fe |
completed | April 29, 2026, 7:07 a.m. |
Created at: April 17, 2026, 6:10 p.m.