Triple
T17231725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class B (Washington area) |
E418255
|
entity |
| Predicate | mapDepiction |
P58961
|
FINISHED |
| Object | sectional aeronautical charts |
—
|
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: sectional aeronautical charts | Statement: [Class B (Washington area), mapDepiction, sectional aeronautical charts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mapDepiction Context triple: [Class B (Washington area), mapDepiction, sectional aeronautical charts]
-
A.
mapsDepict
chosen
Indicates that maps visually represent or illustrate the geographic features, locations, or spatial relationships of something.
-
B.
mapDisplay
Indicates that something is being visually represented or shown on a map interface.
-
C.
mapUse
Indicates a relationship where one entity uses, applies, or employs a map (or mapping) to perform an action or achieve a purpose.
-
D.
mapNumber
Indicates a correspondence where each element in one set or collection is assigned a specific numeric value in another set or domain.
-
E.
mapsAs
Indicates that one entity serves as a mapping or correspondence to another, typically translating or associating elements from one domain or representation to another.
- 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_69d886d8e96081909870bff6c3d0bf09 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42df7da748190a3a1762a67eb871b |
completed | April 19, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69e3832553ac819091aa917c84f755b6 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.