Triple
T2222556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir John Copley |
E48173
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Copley |
E134784
|
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: Copley | Statement: [Sir John Copley, familyName, Copley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Copley Context triple: [Sir John Copley, familyName, Copley]
-
A.
Copley
chosen
Copley is a major MBTA subway station in Boston’s Back Bay neighborhood, serving as a key transfer and access point for nearby landmarks such as Copley Square and the Boston Public Library.
-
B.
Woodmere
Woodmere is a small suburban village located in Cuyahoga County, Ohio, known primarily as a residential and retail community near Cleveland.
-
C.
Charlestown
Charlestown is a district in north Manchester, England, known as a primarily residential area with local amenities and community facilities.
-
D.
Charlestown
Charlestown is the main town and administrative center of the Caribbean island of Nevis, known for its colonial architecture and historic hot springs.
-
E.
Peabody
Peabody is a suburban city in northeastern Massachusetts known for its location on the North Shore and its historical ties to the leather industry.
- 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_69a88aa1ee708190862c8c378c41e9eb |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03bfdd48190bfb96ec3e41c22dc |
completed | March 7, 2026, 6:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae65605fa481908ac5b9d837600626 |
completed | March 9, 2026, 6:14 a.m. |
Created at: March 4, 2026, 7:47 p.m.