Triple
T626183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route 28 (Massachusetts) |
E15824
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Norfolk County |
E4305
|
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: Norfolk County | Statement: [Route 28 (Massachusetts), passesThrough, Norfolk County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norfolk County Context triple: [Route 28 (Massachusetts), passesThrough, Norfolk County]
-
A.
Norfolk County
chosen
Norfolk County is a county in eastern Massachusetts that includes a mix of suburban communities and key urban institutions just outside Boston.
-
B.
Suffolk
Suffolk is a historic rural county in eastern England known for its coastal towns, medieval villages, and agricultural landscapes.
-
C.
Hampshire
Hampshire is a county on England’s south coast known for its historic cities, naval and military heritage, and mix of rural countryside and coastal areas.
-
D.
Sussex County
Sussex County is a county in the southern part of the U.S. state of Delaware, known for its coastal resorts, agriculture, and historic towns.
-
E.
Somerset County
Somerset County is a rural, mountainous county in southwestern Pennsylvania known for its outdoor recreation, wind farms, and historic sites such as the Flight 93 National Memorial.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e587c448190987943a6aad209d1 |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad5897c8488190b5266a04150f81de |
completed | March 8, 2026, 11:08 a.m. |
Created at: March 1, 2026, 7:35 p.m.