Triple
T2527637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southfield |
E56075
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Berkley |
E210607
|
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: Berkley | Statement: [Southfield, borders, Berkley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Berkley Context triple: [Southfield, borders, Berkley]
-
A.
Berkley
Berkley is a small rural town in Bristol County, Massachusetts, known for its quiet residential character and proximity to the Taunton River.
-
B.
Berkley, Michigan
chosen
Berkley, Michigan is a small suburban city in Oakland County known for its tree-lined neighborhoods, family-friendly community, and proximity to Detroit.
-
C.
Everett
Everett is a city in Middlesex County, Massachusetts, located just north of Boston and known for its industrial history and urban residential character.
-
D.
Everett
Everett is a surname of English origin borne by various notable individuals, including American politician and orator Edward Everett.
-
E.
Everett
Everett is a city in western Washington State, known as a major industrial and maritime hub north of Seattle and home to a large Boeing aircraft assembly plant.
- 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_69ab4a48e4f081908f1218d244608659 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd257ea908190a010c0b785853546 |
completed | March 7, 2026, 7:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af655441b0819088b86498520ee3b4 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:46 p.m.