Triple
T7423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cape Cod |
E148
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Massachusetts |
E37
|
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: Massachusetts | Statement: [Cape Cod, locatedIn, Massachusetts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Massachusetts Context triple: [Cape Cod, locatedIn, Massachusetts]
-
A.
Massachusetts
chosen
Massachusetts is a U.S. state in New England known for its pivotal role in American history, prestigious universities, and major cultural and economic centers like Boston.
-
B.
New Hampshire
New Hampshire is a small New England state in the northeastern United States known for its mountainous landscapes, early presidential primary, and “Live Free or Die” motto.
-
C.
Connecticut
Connecticut is a small New England state in the northeastern United States known for its colonial history, affluent suburbs, and role as a financial and educational hub.
-
D.
Maryland
Maryland is a Mid-Atlantic U.S. state known for its Chesapeake Bay shoreline, colonial history, and proximity to the nation’s capital.
-
E.
Vermont
Vermont is a small, rural New England state in the northeastern United States, known for its Green Mountains, maple syrup production, and picturesque towns.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a23ff1903c8190a7d1051b4795eecd |
completed | Feb. 28, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2f0b0d5f481909987c4d937c7157a |
completed | Feb. 28, 2026, 1:42 p.m. |
Created at: Feb. 28, 2026, 12:54 a.m.