Triple
T23183496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kikuchi lines in electron diffraction |
E579522
|
entity |
| Predicate | intersectionsCorrespondTo |
P102344
|
FINISHED |
| Object | zone axes |
—
|
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: zone axes | Statement: [Kikuchi lines in electron diffraction, intersectionsCorrespondTo, zone axes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intersectionsCorrespondTo Context triple: [Kikuchi lines in electron diffraction, intersectionsCorrespondTo, zone axes]
-
A.
isIntersectionOf
chosen
Indicates that something is the exact common part shared by two or more other things, typically where they overlap or meet.
-
B.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
C.
servesIntersection
Indicates that one entity provides service or operational coverage to a specific road or transit intersection.
-
D.
boardIntersectionCount
Indicates the number of distinct points or areas where two or more boards intersect or overlap.
-
E.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f705c14819082c8580a03ed6286 |
completed | April 29, 2026, 4:56 a.m. |
| PD | Predicate disambiguation | batch_69ef8a041c0081909afb670d17a5aaba |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:05 p.m.