Triple
T34672261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4R |
E890405
|
entity |
| Predicate | hasReciprocalHeading |
P53416
|
FINISHED |
| Object | approximately 220 degrees magnetic |
—
|
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 220 degrees magnetic | Statement: [4R, hasReciprocalHeading, approximately 220 degrees magnetic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReciprocalHeading Context triple: [4R, hasReciprocalHeading, approximately 220 degrees magnetic]
-
A.
hasReciprocalMagneticHeadingApprox
chosen
Indicates that two entities have magnetic headings that are approximately reciprocal (differing by about 180 degrees from each other).
-
B.
hasRelationToTrueHeading
Indicates that an entity has a specified relationship or correspondence to a true (reference) heading or direction.
-
C.
hasReciprocalRightDesignation
Indicates that one entity is formally designated as having reciprocal rights or entitlements in relation to another entity.
-
D.
reciprocalOrientation
Indicates that two entities are oriented toward each other in a mutually corresponding or opposite directional alignment.
-
E.
hasReverse
Indicates that one entity serves as the inverse or opposite counterpart of another entity in a given relationship or operation.
- 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_69f349d9c59481908b36baa0be093aea |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:05 a.m.