Triple
T28186018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Audubon Christmas Bird Count |
E716178
|
entity |
| Predicate | countCircleDiameter |
P7302
|
FINISHED |
| Object | 15 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: 15 miles | Statement: [Audubon Christmas Bird Count, countCircleDiameter, 15 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countCircleDiameter Context triple: [Audubon Christmas Bird Count, countCircleDiameter, 15 miles]
-
A.
円の直径比率
Indicates the proportional relationship between a circle’s diameter and another referenced measure (such as another diameter or a standard length).
-
B.
sphereDiameter
Indicates the measurement of the distance across a sphere passing through its center, relating the sphere to its diameter.
-
C.
circumference
Indicates the total length around the boundary of a closed curve, typically a circle, relating a shape to the measure of its perimeter.
-
D.
approximateDiameter
chosen
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
E.
circleType
Indicates the specific classification or category of a circle within a given context or system.
- F. None of above.
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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69fdfbafe32081909c62653ff4fc155c |
completed | May 8, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69fdf64db4a881908f8250e24ae3cefb |
completed | May 8, 2026, 2:42 p.m. |
Created at: April 27, 2026, 10:22 p.m.