Triple
T27155410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania–Delaware border |
E682505
|
entity |
| Predicate | approximateArcRadius |
P23277
|
FINISHED |
| Object | 12 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: 12 miles | Statement: [Pennsylvania–Delaware border, approximateArcRadius, 12 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateArcRadius Context triple: [Pennsylvania–Delaware border, approximateArcRadius, 12 miles]
-
A.
approximateRadius
chosen
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
B.
approximateDiameter
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
-
C.
approximateLengthInMeters
Indicates the estimated or roughly measured length of something expressed in meters.
-
D.
curveRadius
Indicates the radius of curvature associated with an object or path, describing how sharply it bends at a given point.
-
E.
approximateSideLengthOrderOfMagnitude
Indicates that one entity’s side length is approximately the same order of magnitude as another entity’s side length, differing by no more than about a factor of ten.
- 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_69eefaceb2a08190b9659b7f730629f5 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7aa699d68819081ed363931894ab3 |
completed | May 3, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
Created at: April 27, 2026, 9:16 a.m.