Triple
T1596024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Head of the Charles Regatta |
E34284
|
entity |
| Predicate | courseLength |
P29682
|
FINISHED |
| Object | approximately 3 miles |
—
|
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: approximately 3 miles | Statement: [Head of the Charles Regatta, courseLength, approximately 3 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: courseLength Context triple: [Head of the Charles Regatta, courseLength, approximately 3 miles]
-
A.
programLength
Indicates the duration or total length of a program, typically measured in time or size.
-
B.
courseType
Indicates the classification or category of a course based on its nature, level, or instructional format.
-
C.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
D.
courseShape
Indicates the geometric layout or configuration that defines the path or outline of a course.
-
E.
sessionLength
Indicates the duration of time that a particular session lasts from start to end.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a916d2fae48190aaac6b2a5e31a7cf |
completed | March 5, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:27 p.m.