Triple
T3458041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Massachusetts |
E72953
|
entity |
| Predicate | hasRegion |
P285
|
FINISHED |
| Object | South Shore |
E33301
|
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: South Shore | Statement: [Massachusetts, hasRegion, South Shore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: South Shore Context triple: [Massachusetts, hasRegion, South Shore]
-
A.
South Shore
chosen
South Shore is a coastal suburban region south of Boston, Massachusetts, known for its residential communities, beaches, and commuter access to the city.
-
B.
South Shore
South Shore is a residential and lakefront community area on the South Side of Chicago known for its diverse population and views of Lake Michigan.
-
C.
North Shore
North Shore is a coastal region in northeastern Massachusetts known for its historic seaside towns, beaches, and proximity to Boston.
-
D.
North Shore
North Shore is a predominantly residential and commercial region on the northern side of Sydney Harbour, known for its affluent suburbs, harbourside views, and leafy streets.
-
E.
North Shore
North Shore is a riverfront neighborhood in Pittsburgh, Pennsylvania, known for its sports stadiums, entertainment venues, and scenic views along the Allegheny and Ohio Rivers.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae36e748190bf20fd3c6de22e19 |
completed | March 8, 2026, 6:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bb904148190858af0bb467f5954 |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 8, 2026, 3:16 p.m.