Triple
T1782260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knickebein |
E39314
|
entity |
| Predicate | beamStructure |
P4336
|
FINISHED |
| Object | two crossing radio beams over target |
—
|
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: two crossing radio beams over target | Statement: [Knickebein, beamStructure, two crossing radio beams over target]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beamStructure Context triple: [Knickebein, beamStructure, two crossing radio beams over target]
-
A.
beamType
Indicates the specific kind or category of beam involved in the relationship or action.
-
B.
beam
chosen
Indicates that one entity emits, directs, or projects a concentrated line or stream (such as light, energy, or information) toward another entity.
-
C.
viaStructure
Indicates that one entity is connected to or accessed through a particular structural element or medium.
-
D.
buildingSection
Indicates a relationship where one entity is a specific section, part, or subdivision of a larger building.
-
E.
segmentStructure
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of another 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_69a88630519c8190a17addd83c4a3ef4 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab74dc9d1481908084ef07872a71f8 |
completed | March 7, 2026, 12:44 a.m. |
| PD | Predicate disambiguation | batch_69aa61cf3ca881908641fd73ce2f7c9d |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.