Triple
T7957635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Quinsigamond |
E184778
|
entity |
| Predicate | hasRowingCourse |
P80018
|
FINISHED |
| Object | 2,000-meter rowing course |
—
|
LITERAL 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: 2,000-meter rowing course | Statement: [Lake Quinsigamond, hasRowingCourse, 2,000-meter rowing course]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRowingCourse Context triple: [Lake Quinsigamond, hasRowingCourse, 2,000-meter rowing course]
-
A.
conferenceRowing
Indicates a relationship where a conference event or organization is engaged in, hosting, or associated with the sport or activity of rowing.
-
B.
hasBoatLine
Indicates that one entity operates, owns, or is associated with a particular boat service or boat route line.
-
C.
hasInshoreRaces
Indicates that an entity conducts or includes races that take place in inshore or nearshore waters.
-
D.
rowedFor
Indicates that one entity served as a rower or member of the rowing team representing another entity, such as an institution, club, or country.
-
E.
usesCanoes
Indicates that one entity makes use of canoes as a means of transport, activity, or operation in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69ca8293a2388190aace944d7ed9c0c0 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b7ebb24819094bc011d51ef63fb |
completed | March 31, 2026, 3:11 a.m. |
| PD | Predicate disambiguation | batch_69cb0473d7dc8190a25d0cf460b9fcbe |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:11 p.m.