Triple
T19632171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becher school |
E471296
|
entity |
| Predicate | visualApproach |
P136767
|
FINISHED |
| Object | taxonomic classification of forms |
—
|
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: taxonomic classification of forms | Statement: [Becher school, visualApproach, taxonomic classification of forms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visualApproach Context triple: [Becher school, visualApproach, taxonomic classification of forms]
-
A.
hasVisualApproachProcedures
Indicates that an entity has associated visual approach procedures defined or available for use.
-
B.
visibilityAltitude
Indicates the altitude at which something becomes visible or can be seen.
-
C.
hasInstrumentApproach
Indicates that an approach procedure to a location or runway is conducted using specified navigation instruments or instrument-based methods.
-
D.
approachControl
Indicates that one entity moves closer to another entity in a deliberate or controlled manner.
-
E.
navigationClearanceImprovedComparedTo
Indicates that the level of navigation clearance in one context is better or less obstructed compared to another context.
- F. None of above. chosen
Provenance (4 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641036ee881909fdd8170fe4cdac9 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
| PDg | Predicate description generation | batch_69e51a23300c8190988552491d9783d7 |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 1:44 p.m.