Triple
T21356396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dartmouth, Nova Scotia |
E526637
|
entity |
| Predicate | nicknamed |
P744
|
FINISHED |
| Object | The City of Lakes |
—
|
NE NERFINISHED |
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: The City of Lakes | Statement: [Dartmouth, Nova Scotia, nicknamed, The City of Lakes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The City of Lakes Context triple: [Dartmouth, Nova Scotia, nicknamed, The City of Lakes]
-
A.
The City of Four Lakes
The City of Four Lakes is a nickname for Madison, Wisconsin, highlighting its distinctive setting amid four interconnected lakes.
-
B.
City of Lakes
City of Lakes is a popular nickname for Minneapolis, highlighting its many urban lakes and waterfronts.
-
C.
City of Lakes
City of Lakes is a popular nickname for Thane, a city in Maharashtra, India, known for its numerous lakes and scenic waterfronts.
-
D.
City of Lakes
City of Lakes is a popular nickname for Udaipur, a picturesque city in Rajasthan, India, renowned for its numerous interconnected lakes and romantic waterfront scenery.
-
E.
City of Lakes
chosen
City of Lakes is the nickname for Dartmouth, Nova Scotia, highlighting its numerous surrounding lakes and waterfronts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8afa0fca481908f1fd02154bcba9f |
completed | April 22, 2026, 11:23 a.m. |
Created at: April 16, 2026, 5:07 p.m.